├── Blogathon ├── Code │ └── Student%score.ipynb ├── Datasets │ └── student_scores.csv ├── Media │ ├── Data.png │ ├── Reg_line.png │ ├── Regression.png │ ├── SLR.mp4 │ ├── Testing sets.png │ ├── Training sets.png │ └── prediction.png └── README.md ├── House-price Prediciton ├── House-price-prediction .ipynb └── README.md ├── KNN Implementation ├── KNN .ipynb └── data.csv ├── Loan Prediction ├── Datasets │ ├── sample_submission_49d68Cx.csv │ ├── test_lAUu6dG.csv │ └── train_ctrUa4K.csv └── LoanPrediction .ipynb ├── PR ├── Datasets │ ├── beer.txt │ ├── heart.csv │ └── training_data.csv └── New Text Document.txt └── README.md /Blogathon/Datasets/student_scores.csv: -------------------------------------------------------------------------------- 1 | Hours,Scores 2 | 2.5,21 3 | 5.1,47 4 | 3.2,27 5 | 8.5,75 6 | 3.5,30 7 | 1.5,20 8 | 9.2,88 9 | 5.5,60 10 | 8.3,81 11 | 2.7,25 12 | 7.7,85 13 | 5.9,62 14 | 4.5,41 15 | 3.3,42 16 | 1.1,17 17 | 8.9,95 18 | 2.5,30 19 | 1.9,24 20 | 6.1,67 21 | 7.4,69 22 | 2.7,30 23 | 4.8,54 24 | 3.8,35 25 | 6.9,76 26 | 7.8,86 27 | -------------------------------------------------------------------------------- /Blogathon/Media/Data.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/Data.png -------------------------------------------------------------------------------- /Blogathon/Media/Reg_line.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/Reg_line.png -------------------------------------------------------------------------------- /Blogathon/Media/Regression.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/Regression.png -------------------------------------------------------------------------------- /Blogathon/Media/SLR.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/SLR.mp4 -------------------------------------------------------------------------------- /Blogathon/Media/Testing sets.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/Testing sets.png -------------------------------------------------------------------------------- /Blogathon/Media/Training sets.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/Training sets.png -------------------------------------------------------------------------------- /Blogathon/Media/prediction.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aj7tt/Machine-learning-Projects/e870dc523deef46c687fb9dcc2a65ac5ab31a842/Blogathon/Media/prediction.png -------------------------------------------------------------------------------- /Blogathon/README.md: -------------------------------------------------------------------------------- 1 | 2 | ### simple Linear regression model (make your first model) 3 | 4 | This project is toward the first step in developing machine learning model using simple Linear regression model 5 | 6 | 7 | 8 | 9 | 👉 Do you need step-wise guide to build a model ? 10 | Reachout to me : [@_aj7t](https://twitter.com/_aj7t ) 11 | -------------------------------------------------------------------------------- /House-price Prediciton/README.md: -------------------------------------------------------------------------------- 1 | 2 | # House Price Predicition 3 | 4 | 5 | ## Requirements 6 | 7 | - Numpy 8 | - Pandas 9 | - Sklearn 10 | - Seaborn 11 | - matplotlib.plt 12 | 13 | ## Model Implementation 14 | 15 | - Linear Regression (Accuracy-75%) 16 | - Polynomial Regression (Accuracy-83%) 17 | - Random Forest (Accuracy - 85%) 18 | -------------------------------------------------------------------------------- /KNN Implementation/KNN .ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "Name :- Ajit kumar \n", 8 | "Roll no :-SCET223 \n", 9 | "Prn no :-0120180520\n" 10 | ] 11 | }, 12 | { 13 | "cell_type": "markdown", 14 | "metadata": { 15 | "colab_type": "text", 16 | "id": "XHyuIcRGixQy" 17 | }, 18 | "source": [ 19 | "# KNN Classification" 20 | ] 21 | }, 22 | { 23 | "cell_type": "markdown", 24 | "metadata": { 25 | "colab_type": "text", 26 | "id": "MetALTTmQKkh" 27 | }, 28 | "source": [ 29 | "### Importing Libraries" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 1, 35 | "metadata": { 36 | "colab": {}, 37 | "colab_type": "code", 38 | "id": "eWchGPfa9xW9" 39 | }, 40 | "outputs": [], 41 | "source": [ 42 | "#importing libraries \n", 43 | "import pandas as pd \n", 44 | "import numpy as np\n", 45 | "import matplotlib.pyplot as plt\n", 46 | "%matplotlib inline\n", 47 | "plt.style.use(['dark_background'])\n", 48 | "import warnings\n", 49 | "warnings.filterwarnings(\"ignore\")" 50 | ] 51 | }, 52 | { 53 | "cell_type": "markdown", 54 | "metadata": { 55 | "colab_type": "text", 56 | "id": "tHKgifnpjyvh" 57 | }, 58 | "source": [ 59 | "### Load the data" 60 | ] 61 | }, 62 | { 63 | "cell_type": "code", 64 | "execution_count": 2, 65 | "metadata": { 66 | "colab": { 67 | "base_uri": "https://localhost:8080/", 68 | "height": 34 69 | }, 70 | "colab_type": "code", 71 | "executionInfo": { 72 | "elapsed": 1296, 73 | "status": "ok", 74 | "timestamp": 1555058105638, 75 | "user": { 76 | "displayName": "Sharoon Saxena", 77 | "photoUrl": "", 78 | "userId": "14774175216384036942" 79 | }, 80 | "user_tz": -330 81 | }, 82 | "id": "NB5xYyHg9xXA", 83 | "outputId": "33bc3be6-c335-4dbc-b57f-730ac784433d" 84 | }, 85 | "outputs": [ 86 | { 87 | "data": { 88 | "text/plain": [ 89 | "(891, 25)" 90 | ] 91 | }, 92 | "execution_count": 2, 93 | "metadata": {}, 94 | "output_type": "execute_result" 95 | } 96 | ], 97 | "source": [ 98 | "data = pd.read_csv('data.csv')\n", 99 | "data.shape" 100 | ] 101 | }, 102 | { 103 | "cell_type": "code", 104 | "execution_count": 3, 105 | "metadata": { 106 | "colab": { 107 | "base_uri": "https://localhost:8080/", 108 | "height": 253 109 | }, 110 | "colab_type": "code", 111 | "executionInfo": { 112 | "elapsed": 1284, 113 | "status": "ok", 114 | "timestamp": 1555058105639, 115 | "user": { 116 | "displayName": "Sharoon Saxena", 117 | "photoUrl": "", 118 | "userId": "14774175216384036942" 119 | }, 120 | "user_tz": -330 121 | }, 122 | "id": "qjISR4M_9xXE", 123 | "outputId": "d45fdb4b-25c5-40d3-edc2-cf524ad16f73" 124 | }, 125 | "outputs": [ 126 | { 127 | "data": { 128 | "text/html": [ 129 | "
\n", 130 | "\n", 143 | "\n", 144 | " \n", 145 | " \n", 146 | " \n", 147 | " \n", 148 | " \n", 149 | " \n", 150 | " \n", 151 | " \n", 152 | " \n", 153 | " \n", 154 | " \n", 155 | " \n", 156 | " \n", 157 | " \n", 158 | " \n", 159 | " \n", 160 | " \n", 161 | " \n", 162 | " \n", 163 | " \n", 164 | " \n", 165 | " \n", 166 | " \n", 167 | " \n", 168 | " \n", 169 | " \n", 170 | " \n", 171 | " \n", 172 | " \n", 173 | " \n", 174 | " \n", 175 | " \n", 176 | " \n", 177 | " \n", 178 | " \n", 179 | " \n", 180 | " \n", 181 | " \n", 182 | " \n", 183 | " \n", 184 | " \n", 185 | " \n", 186 | " \n", 187 | " \n", 188 | " \n", 189 | " \n", 190 | " \n", 191 | " \n", 192 | " \n", 193 | " \n", 194 | " \n", 195 | " \n", 196 | " \n", 197 | " \n", 198 | " \n", 199 | " \n", 200 | " \n", 201 | " \n", 202 | " \n", 203 | " \n", 204 | " \n", 205 | " \n", 206 | " \n", 207 | " \n", 208 | " \n", 209 | " \n", 210 | " \n", 211 | " \n", 212 | " \n", 213 | " \n", 214 | " \n", 215 | " \n", 216 | " \n", 217 | " \n", 218 | " \n", 219 | " \n", 220 | " \n", 221 | " \n", 222 | " \n", 223 | " \n", 224 | " \n", 225 | " \n", 226 | " \n", 227 | " \n", 228 | " \n", 229 | " \n", 230 | " \n", 231 | " \n", 232 | " \n", 233 | " \n", 234 | " \n", 235 | " \n", 236 | " \n", 237 | " \n", 238 | " \n", 239 | " \n", 240 | " \n", 241 | " \n", 242 | " \n", 243 | " \n", 244 | " \n", 245 | " \n", 246 | " \n", 247 | " \n", 248 | " \n", 249 | " \n", 250 | " \n", 251 | " \n", 252 | " \n", 253 | " \n", 254 | " \n", 255 | " \n", 256 | " \n", 257 | " \n", 258 | " \n", 259 | " \n", 260 | " \n", 261 | " \n", 262 | " \n", 263 | " \n", 264 | " \n", 265 | " \n", 266 | " \n", 267 | " \n", 268 | " \n", 269 | " \n", 270 | " \n", 271 | " \n", 272 | " \n", 273 | " \n", 274 | " \n", 275 | " \n", 276 | " \n", 277 | " \n", 278 | " \n", 279 | " \n", 280 | " \n", 281 | " \n", 282 | " \n", 283 | " \n", 284 | " \n", 285 | " \n", 286 | " \n", 287 | " \n", 288 | " \n", 289 | " \n", 290 | " \n", 291 | " \n", 292 | "
SurvivedAgeFarePclass_1Pclass_2Pclass_3Sex_femaleSex_maleSibSp_0SibSp_1...Parch_0Parch_1Parch_2Parch_3Parch_4Parch_5Parch_6Embarked_CEmbarked_QEmbarked_S
0022.07.25000010101...1000000001
1138.071.28331001001...1000000100
2126.07.92500011010...1000000001
3135.053.10001001001...1000000001
4035.08.05000010110...1000000001
\n", 293 | "

5 rows × 25 columns

\n", 294 | "
" 295 | ], 296 | "text/plain": [ 297 | " Survived Age Fare Pclass_1 Pclass_2 Pclass_3 Sex_female \\\n", 298 | "0 0 22.0 7.2500 0 0 1 0 \n", 299 | "1 1 38.0 71.2833 1 0 0 1 \n", 300 | "2 1 26.0 7.9250 0 0 1 1 \n", 301 | "3 1 35.0 53.1000 1 0 0 1 \n", 302 | "4 0 35.0 8.0500 0 0 1 0 \n", 303 | "\n", 304 | " Sex_male SibSp_0 SibSp_1 ... Parch_0 Parch_1 Parch_2 Parch_3 \\\n", 305 | "0 1 0 1 ... 1 0 0 0 \n", 306 | "1 0 0 1 ... 1 0 0 0 \n", 307 | "2 0 1 0 ... 1 0 0 0 \n", 308 | "3 0 0 1 ... 1 0 0 0 \n", 309 | "4 1 1 0 ... 1 0 0 0 \n", 310 | "\n", 311 | " Parch_4 Parch_5 Parch_6 Embarked_C Embarked_Q Embarked_S \n", 312 | "0 0 0 0 0 0 1 \n", 313 | "1 0 0 0 1 0 0 \n", 314 | "2 0 0 0 0 0 1 \n", 315 | "3 0 0 0 0 0 1 \n", 316 | "4 0 0 0 0 0 1 \n", 317 | "\n", 318 | "[5 rows x 25 columns]" 319 | ] 320 | }, 321 | "execution_count": 3, 322 | "metadata": {}, 323 | "output_type": "execute_result" 324 | } 325 | ], 326 | "source": [ 327 | "data.head()" 328 | ] 329 | }, 330 | { 331 | "cell_type": "markdown", 332 | "metadata": { 333 | "colab_type": "text", 334 | "id": "hGxgnJmxj3nv" 335 | }, 336 | "source": [ 337 | "### Segregating variables: Independent and Dependent Variables" 338 | ] 339 | }, 340 | { 341 | "cell_type": "code", 342 | "execution_count": 4, 343 | "metadata": { 344 | "colab": { 345 | "base_uri": "https://localhost:8080/", 346 | "height": 34 347 | }, 348 | "colab_type": "code", 349 | "executionInfo": { 350 | "elapsed": 1974, 351 | "status": "ok", 352 | "timestamp": 1555058106339, 353 | "user": { 354 | "displayName": "Sharoon Saxena", 355 | "photoUrl": "", 356 | "userId": "14774175216384036942" 357 | }, 358 | "user_tz": -330 359 | }, 360 | "id": "rym4fnPq9xXG", 361 | "outputId": "8eb99fe6-c327-4541-bd1e-fd89e69b13fd" 362 | }, 363 | "outputs": [ 364 | { 365 | "data": { 366 | "text/plain": [ 367 | "((891, 24), (891,))" 368 | ] 369 | }, 370 | "execution_count": 4, 371 | "metadata": {}, 372 | "output_type": "execute_result" 373 | } 374 | ], 375 | "source": [ 376 | "#seperating independent and dependent variables\n", 377 | "x = data.drop(['Survived'], axis=1)\n", 378 | "y = data['Survived']\n", 379 | "x.shape, y.shape" 380 | ] 381 | }, 382 | { 383 | "cell_type": "markdown", 384 | "metadata": { 385 | "colab_type": "text", 386 | "id": "YXztAQ_Ded3q" 387 | }, 388 | "source": [ 389 | "### Scaling the data (Using MinMax Scaler)" 390 | ] 391 | }, 392 | { 393 | "cell_type": "code", 394 | "execution_count": 5, 395 | "metadata": { 396 | "colab": { 397 | "base_uri": "https://localhost:8080/", 398 | "height": 85 399 | }, 400 | "colab_type": "code", 401 | "executionInfo": { 402 | "elapsed": 1954, 403 | "status": "ok", 404 | "timestamp": 1555058106340, 405 | "user": { 406 | "displayName": "Sharoon Saxena", 407 | "photoUrl": "", 408 | "userId": "14774175216384036942" 409 | }, 410 | "user_tz": -330 411 | }, 412 | "id": "mBlVReHxd2eb", 413 | "outputId": "488f8b5e-e1d9-4d11-dd45-5295f2cb7b0e" 414 | }, 415 | "outputs": [], 416 | "source": [ 417 | "## Importing the MinMax Scaler\n", 418 | "from sklearn.preprocessing import MinMaxScaler\n", 419 | "scaler = MinMaxScaler()\n", 420 | "x_scaled = scaler.fit_transform(x)" 421 | ] 422 | }, 423 | { 424 | "cell_type": "code", 425 | "execution_count": 6, 426 | "metadata": {}, 427 | "outputs": [], 428 | "source": [ 429 | "x = pd.DataFrame(x_scaled, columns = x.columns)" 430 | ] 431 | }, 432 | { 433 | "cell_type": "code", 434 | "execution_count": 7, 435 | "metadata": {}, 436 | "outputs": [ 437 | { 438 | "data": { 439 | "text/html": [ 440 | "
\n", 441 | "\n", 454 | "\n", 455 | " \n", 456 | " \n", 457 | " \n", 458 | " \n", 459 | " \n", 460 | " \n", 461 | " \n", 462 | " \n", 463 | " \n", 464 | " \n", 465 | " \n", 466 | " \n", 467 | " \n", 468 | " \n", 469 | " \n", 470 | " \n", 471 | " \n", 472 | " \n", 473 | " \n", 474 | " \n", 475 | " \n", 476 | " \n", 477 | " \n", 478 | " \n", 479 | " \n", 480 | " \n", 481 | " \n", 482 | " \n", 483 | " \n", 484 | " \n", 485 | " \n", 486 | " \n", 487 | " \n", 488 | " \n", 489 | " \n", 490 | " \n", 491 | " \n", 492 | " \n", 493 | " \n", 494 | " \n", 495 | " \n", 496 | " \n", 497 | " \n", 498 | " \n", 499 | " \n", 500 | " \n", 501 | " \n", 502 | " \n", 503 | " \n", 504 | " \n", 505 | " \n", 506 | " \n", 507 | " \n", 508 | " \n", 509 | " \n", 510 | " \n", 511 | " \n", 512 | " \n", 513 | " \n", 514 | " \n", 515 | " \n", 516 | " \n", 517 | " \n", 518 | " \n", 519 | " \n", 520 | " \n", 521 | " \n", 522 | " \n", 523 | " \n", 524 | " \n", 525 | " \n", 526 | " \n", 527 | " \n", 528 | " \n", 529 | " \n", 530 | " \n", 531 | " \n", 532 | " \n", 533 | " \n", 534 | " \n", 535 | " \n", 536 | " \n", 537 | " \n", 538 | " \n", 539 | " \n", 540 | " \n", 541 | " \n", 542 | " \n", 543 | " \n", 544 | " \n", 545 | " \n", 546 | " \n", 547 | " \n", 548 | " \n", 549 | " \n", 550 | " \n", 551 | " \n", 552 | " \n", 553 | " \n", 554 | " \n", 555 | " \n", 556 | " \n", 557 | " \n", 558 | " \n", 559 | " \n", 560 | " \n", 561 | " \n", 562 | " \n", 563 | " \n", 564 | " \n", 565 | " \n", 566 | " \n", 567 | " \n", 568 | " \n", 569 | " \n", 570 | " \n", 571 | " \n", 572 | " \n", 573 | " \n", 574 | " \n", 575 | " \n", 576 | " \n", 577 | " \n", 578 | " \n", 579 | " \n", 580 | " \n", 581 | " \n", 582 | " \n", 583 | " \n", 584 | " \n", 585 | " \n", 586 | " \n", 587 | " \n", 588 | " \n", 589 | " \n", 590 | " \n", 591 | " \n", 592 | " \n", 593 | " \n", 594 | " \n", 595 | " \n", 596 | " \n", 597 | " \n", 598 | " \n", 599 | " \n", 600 | " \n", 601 | " \n", 602 | " \n", 603 | "
AgeFarePclass_1Pclass_2Pclass_3Sex_femaleSex_maleSibSp_0SibSp_1SibSp_2...Parch_0Parch_1Parch_2Parch_3Parch_4Parch_5Parch_6Embarked_CEmbarked_QEmbarked_S
00.2711740.0141510.00.01.00.01.00.01.00.0...1.00.00.00.00.00.00.00.00.01.0
10.4722290.1391361.00.00.01.00.00.01.00.0...1.00.00.00.00.00.00.01.00.00.0
20.3214380.0154690.00.01.01.00.01.00.00.0...1.00.00.00.00.00.00.00.00.01.0
30.4345310.1036441.00.00.01.00.00.01.00.0...1.00.00.00.00.00.00.00.00.01.0
40.4345310.0157130.00.01.00.01.01.00.00.0...1.00.00.00.00.00.00.00.00.01.0
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5 rows × 24 columns

\n", 605 | "
" 606 | ], 607 | "text/plain": [ 608 | " Age Fare Pclass_1 Pclass_2 Pclass_3 Sex_female Sex_male \\\n", 609 | "0 0.271174 0.014151 0.0 0.0 1.0 0.0 1.0 \n", 610 | "1 0.472229 0.139136 1.0 0.0 0.0 1.0 0.0 \n", 611 | "2 0.321438 0.015469 0.0 0.0 1.0 1.0 0.0 \n", 612 | "3 0.434531 0.103644 1.0 0.0 0.0 1.0 0.0 \n", 613 | "4 0.434531 0.015713 0.0 0.0 1.0 0.0 1.0 \n", 614 | "\n", 615 | " SibSp_0 SibSp_1 SibSp_2 ... Parch_0 Parch_1 Parch_2 Parch_3 \\\n", 616 | "0 0.0 1.0 0.0 ... 1.0 0.0 0.0 0.0 \n", 617 | "1 0.0 1.0 0.0 ... 1.0 0.0 0.0 0.0 \n", 618 | "2 1.0 0.0 0.0 ... 1.0 0.0 0.0 0.0 \n", 619 | "3 0.0 1.0 0.0 ... 1.0 0.0 0.0 0.0 \n", 620 | "4 1.0 0.0 0.0 ... 1.0 0.0 0.0 0.0 \n", 621 | "\n", 622 | " Parch_4 Parch_5 Parch_6 Embarked_C Embarked_Q Embarked_S \n", 623 | "0 0.0 0.0 0.0 0.0 0.0 1.0 \n", 624 | "1 0.0 0.0 0.0 1.0 0.0 0.0 \n", 625 | "2 0.0 0.0 0.0 0.0 0.0 1.0 \n", 626 | "3 0.0 0.0 0.0 0.0 0.0 1.0 \n", 627 | "4 0.0 0.0 0.0 0.0 0.0 1.0 \n", 628 | "\n", 629 | "[5 rows x 24 columns]" 630 | ] 631 | }, 632 | "execution_count": 7, 633 | "metadata": {}, 634 | "output_type": "execute_result" 635 | } 636 | ], 637 | "source": [ 638 | "x.head()" 639 | ] 640 | }, 641 | { 642 | "cell_type": "code", 643 | "execution_count": 8, 644 | "metadata": { 645 | "colab": {}, 646 | "colab_type": "code", 647 | "id": "-PcDK1re9xXM" 648 | }, 649 | "outputs": [], 650 | "source": [ 651 | "# Importing the train test split function\n", 652 | "from sklearn.model_selection import train_test_split\n", 653 | "train_x,test_x,train_y,test_y = train_test_split(x,y, random_state = 56, stratify=y)" 654 | ] 655 | }, 656 | { 657 | "cell_type": "code", 658 | "execution_count": 9, 659 | "metadata": {}, 660 | "outputs": [ 661 | { 662 | "name": "stdout", 663 | "output_type": "stream", 664 | "text": [ 665 | "(668, 24)\n", 666 | "(223, 24)\n" 667 | ] 668 | } 669 | ], 670 | "source": [ 671 | "# print the shapes of the new X objects\n", 672 | "print(train_x.shape)\n", 673 | "print(test_x.shape)" 674 | ] 675 | }, 676 | { 677 | "cell_type": "code", 678 | "execution_count": 10, 679 | "metadata": {}, 680 | "outputs": [ 681 | { 682 | "name": "stdout", 683 | "output_type": "stream", 684 | "text": [ 685 | "(668,)\n", 686 | "(223,)\n" 687 | ] 688 | } 689 | ], 690 | "source": [ 691 | "# print the shapes of the new y objects\n", 692 | "print(train_y.shape)\n", 693 | "print(test_y.shape)" 694 | ] 695 | }, 696 | { 697 | "cell_type": "markdown", 698 | "metadata": { 699 | "colab_type": "text", 700 | "id": "WvsDKzjdyNWi" 701 | }, 702 | "source": [ 703 | "### Implementing KNN Classifier" 704 | ] 705 | }, 706 | { 707 | "cell_type": "code", 708 | "execution_count": 11, 709 | "metadata": { 710 | "colab": {}, 711 | "colab_type": "code", 712 | "id": "yCG2gM5KyM-1" 713 | }, 714 | "outputs": [], 715 | "source": [ 716 | "#importing KNN classifier and metric F1score\n", 717 | "from sklearn.neighbors import KNeighborsClassifier as KNN\n", 718 | "from sklearn.metrics import f1_score" 719 | ] 720 | }, 721 | { 722 | "cell_type": "code", 723 | "execution_count": 12, 724 | "metadata": { 725 | "colab": { 726 | "base_uri": "https://localhost:8080/", 727 | "height": 51 728 | }, 729 | "colab_type": "code", 730 | "executionInfo": { 731 | "elapsed": 1923, 732 | "status": "ok", 733 | "timestamp": 1555058106343, 734 | "user": { 735 | "displayName": "Sharoon Saxena", 736 | "photoUrl": "", 737 | "userId": "14774175216384036942" 738 | }, 739 | "user_tz": -330 740 | }, 741 | "id": "TFrwDTRdybYF", 742 | "outputId": "017cef2e-c310-40ae-d17e-bb49c4ddb1b3" 743 | }, 744 | "outputs": [ 745 | { 746 | "data": { 747 | "text/plain": [ 748 | "KNeighborsClassifier()" 749 | ] 750 | }, 751 | "execution_count": 12, 752 | "metadata": {}, 753 | "output_type": "execute_result" 754 | } 755 | ], 756 | "source": [ 757 | "# Creating instance of KNN\n", 758 | "clf = KNN(n_neighbors = 5)\n", 759 | "\n", 760 | "# Fitting the model\n", 761 | "clf.fit(train_x, train_y)" 762 | ] 763 | }, 764 | { 765 | "cell_type": "code", 766 | "execution_count": 13, 767 | "metadata": {}, 768 | "outputs": [ 769 | { 770 | "name": "stdout", 771 | "output_type": "stream", 772 | "text": [ 773 | "Test F1 Score = 0.6785714285714285\n" 774 | ] 775 | } 776 | ], 777 | "source": [ 778 | "# Predicting over the Train Set and calculating F1 for k=5\n", 779 | "test_predict = clf.predict(test_x)\n", 780 | "k = f1_score(test_predict, test_y)\n", 781 | "print('Test F1 Score = ', k )" 782 | ] 783 | }, 784 | { 785 | "cell_type": "markdown", 786 | "metadata": { 787 | "colab_type": "text", 788 | "id": "WUlYDj9Xkmvy" 789 | }, 790 | "source": [ 791 | "### Elbow for Classifier\n", 792 | " the optimal value of K" 793 | ] 794 | }, 795 | { 796 | "cell_type": "code", 797 | "execution_count": 14, 798 | "metadata": { 799 | "colab": {}, 800 | "colab_type": "code", 801 | "id": "8NpQ3BLz-soi" 802 | }, 803 | "outputs": [], 804 | "source": [ 805 | "def Elbow(K):\n", 806 | " #initiating empty list\n", 807 | " test_error = []\n", 808 | " \n", 809 | " #training model for evey value of K\n", 810 | " for i in K:\n", 811 | " #Instance oh KNN\n", 812 | " clf = KNN(n_neighbors = i)\n", 813 | " clf.fit(train_x, train_y)\n", 814 | " # Appending F1 scores to empty list claculated using the predictions\n", 815 | " tmp = clf.predict(test_x)\n", 816 | " tmp = f1_score(tmp,test_y)\n", 817 | " error = 1-tmp\n", 818 | " test_error.append(error)\n", 819 | " \n", 820 | " return test_error" 821 | ] 822 | }, 823 | { 824 | "cell_type": "code", 825 | "execution_count": 15, 826 | "metadata": { 827 | "colab": {}, 828 | "colab_type": "code", 829 | "id": "61WGHNM_Cxn2" 830 | }, 831 | "outputs": [], 832 | "source": [ 833 | "#Defining K range\n", 834 | "k = range(6, 20, 2)" 835 | ] 836 | }, 837 | { 838 | "cell_type": "code", 839 | "execution_count": 16, 840 | "metadata": { 841 | "colab": {}, 842 | "colab_type": "code", 843 | "id": "SNBDTcSf9xXW" 844 | }, 845 | "outputs": [], 846 | "source": [ 847 | "# calling above defined function\n", 848 | "test = Elbow(k)" 849 | ] 850 | }, 851 | { 852 | "cell_type": "code", 853 | "execution_count": 17, 854 | "metadata": { 855 | "colab": { 856 | "base_uri": "https://localhost:8080/", 857 | "height": 312 858 | }, 859 | "colab_type": "code", 860 | "executionInfo": { 861 | "elapsed": 2854, 862 | "status": "ok", 863 | "timestamp": 1555058107314, 864 | "user": { 865 | "displayName": "Sharoon Saxena", 866 | "photoUrl": "", 867 | "userId": "14774175216384036942" 868 | }, 869 | "user_tz": -330 870 | }, 871 | "id": "6iA6n55NDKJf", 872 | "outputId": "bb6700af-e76f-433f-b81e-92537cb3a60c", 873 | "scrolled": true 874 | }, 875 | "outputs": [ 876 | { 877 | "data": { 878 | "text/plain": [ 879 | "Text(0.5, 1.0, 'Elbow Curve for test')" 880 | ] 881 | }, 882 | "execution_count": 17, 883 | "metadata": {}, 884 | "output_type": "execute_result" 885 | }, 886 | { 887 | "data": { 888 | "image/png": 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\n", 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" 891 | ] 892 | }, 893 | "metadata": {}, 894 | "output_type": "display_data" 895 | } 896 | ], 897 | "source": [ 898 | "# plotting the Curves\n", 899 | "plt.plot(k, test)\n", 900 | "plt.xlabel('K Neighbors')\n", 901 | "plt.ylabel('Test error')\n", 902 | "plt.title('Elbow Curve for test')" 903 | ] 904 | }, 905 | { 906 | "cell_type": "code", 907 | "execution_count": 18, 908 | "metadata": { 909 | "colab": { 910 | "base_uri": "https://localhost:8080/", 911 | "height": 51 912 | }, 913 | "colab_type": "code", 914 | "executionInfo": { 915 | "elapsed": 1923, 916 | "status": "ok", 917 | "timestamp": 1555058106343, 918 | "user": { 919 | "displayName": "Sharoon Saxena", 920 | "photoUrl": "", 921 | "userId": "14774175216384036942" 922 | }, 923 | "user_tz": -330 924 | }, 925 | "id": "TFrwDTRdybYF", 926 | "outputId": "017cef2e-c310-40ae-d17e-bb49c4ddb1b3" 927 | }, 928 | "outputs": [ 929 | { 930 | "name": "stdout", 931 | "output_type": "stream", 932 | "text": [ 933 | "Test F1 Score 0.7037037037037037\n" 934 | ] 935 | } 936 | ], 937 | "source": [ 938 | "# Creating instance of KNN at 14\n", 939 | "clf = KNN(n_neighbors = 14)\n", 940 | "\n", 941 | "# Fitting the model\n", 942 | "clf.fit(train_x, train_y)\n", 943 | "\n", 944 | "# Predicting over the Train Set and calculating F1\n", 945 | "test_predict = clf.predict(test_x)\n", 946 | "k = f1_score(test_predict, test_y)\n", 947 | "print('Test F1 Score ', k )" 948 | ] 949 | }, 950 | { 951 | "cell_type": "code", 952 | "execution_count": 19, 953 | "metadata": {}, 954 | "outputs": [ 955 | { 956 | "data": { 957 | "text/plain": [ 958 | "array([0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1,\n", 959 | " 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1,\n", 960 | " 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", 961 | " 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0,\n", 962 | " 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,\n", 963 | " 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0,\n", 964 | " 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,\n", 965 | " 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1,\n", 966 | " 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1,\n", 967 | " 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,\n", 968 | " 0, 0, 1], dtype=int64)" 969 | ] 970 | }, 971 | "execution_count": 19, 972 | "metadata": {}, 973 | "output_type": "execute_result" 974 | } 975 | ], 976 | "source": [ 977 | "# train the model with X and y (not X_train and y_train)\n", 978 | "clf.fit(x, y)\n", 979 | "\n", 980 | "# make a prediction for an out-of-sample observation\n", 981 | "pred=clf.predict(test_x)\n", 982 | "pred" 983 | ] 984 | }, 985 | { 986 | "cell_type": "raw", 987 | "metadata": {}, 988 | "source": [] 989 | }, 990 | { 991 | "cell_type": "code", 992 | "execution_count": 20, 993 | "metadata": {}, 994 | "outputs": [ 995 | { 996 | "data": { 997 | "text/html": [ 998 | "
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Actualpredicted
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223 rows × 2 columns

\n", 1079 | "
" 1080 | ], 1081 | "text/plain": [ 1082 | " Actual predicted\n", 1083 | "560 0 0\n", 1084 | "582 0 0\n", 1085 | "546 1 1\n", 1086 | "575 0 0\n", 1087 | "460 1 0\n", 1088 | ".. ... ...\n", 1089 | "139 0 0\n", 1090 | "344 0 0\n", 1091 | "551 0 0\n", 1092 | "382 0 0\n", 1093 | "274 1 1\n", 1094 | "\n", 1095 | "[223 rows x 2 columns]" 1096 | ] 1097 | }, 1098 | "execution_count": 20, 1099 | "metadata": {}, 1100 | "output_type": "execute_result" 1101 | } 1102 | ], 1103 | "source": [ 1104 | "# Comparing Actual vs Predicted\n", 1105 | "\n", 1106 | "df=pd.DataFrame({\"Actual\":test_y,\"predicted\":test_predict})\n", 1107 | "df" 1108 | ] 1109 | }, 1110 | { 1111 | "cell_type": "raw", 1112 | "metadata": {}, 1113 | "source": [] 1114 | }, 1115 | { 1116 | "cell_type": "raw", 1117 | "metadata": {}, 1118 | "source": [] 1119 | } 1120 | ], 1121 | "metadata": { 1122 | "colab": { 1123 | "collapsed_sections": [], 1124 | "name": "KNN Imple.ipynb", 1125 | "provenance": [], 1126 | "version": "0.3.2" 1127 | }, 1128 | "kernelspec": { 1129 | "display_name": "Python 3", 1130 | "language": "python", 1131 | "name": "python3" 1132 | }, 1133 | "language_info": { 1134 | "codemirror_mode": { 1135 | "name": "ipython", 1136 | "version": 3 1137 | }, 1138 | "file_extension": ".py", 1139 | "mimetype": "text/x-python", 1140 | "name": "python", 1141 | "nbconvert_exporter": "python", 1142 | "pygments_lexer": "ipython3", 1143 | "version": "3.8.3" 1144 | } 1145 | }, 1146 | "nbformat": 4, 1147 | "nbformat_minor": 1 1148 | } 1149 | -------------------------------------------------------------------------------- /KNN Implementation/data.csv: -------------------------------------------------------------------------------- 1 | Survived,Age,Fare,Pclass_1,Pclass_2,Pclass_3,Sex_female,Sex_male,SibSp_0,SibSp_1,SibSp_2,SibSp_3,SibSp_4,SibSp_5,SibSp_8,Parch_0,Parch_1,Parch_2,Parch_3,Parch_4,Parch_5,Parch_6,Embarked_C,Embarked_Q,Embarked_S 2 | 0,22.0,7.25,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 3 | 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1,38.0,80.0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 64 | 0,45.0,83.475,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 65 | 0,4.0,27.9,0,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 66 | 0,29.69911764705882,27.7208,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 67 | 1,29.69911764705882,15.2458,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 68 | 1,29.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 69 | 0,19.0,8.1583,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 70 | 1,17.0,7.925,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 71 | 0,26.0,8.6625,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 72 | 0,32.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 73 | 0,16.0,46.9,0,0,1,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1 74 | 0,21.0,73.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 75 | 0,26.0,14.4542,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 76 | 1,32.0,56.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 77 | 0,25.0,7.65,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 78 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 79 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 80 | 1,0.83,29.0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 81 | 1,30.0,12.475,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 82 | 0,22.0,9.0,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 83 | 1,29.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 84 | 1,29.69911764705882,7.7875,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 85 | 0,28.0,47.1,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 86 | 1,17.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 87 | 1,33.0,15.85,0,0,1,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1 88 | 0,16.0,34.375,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1 89 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 90 | 1,23.0,263.0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 91 | 0,24.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 92 | 0,29.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 93 | 0,20.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 94 | 0,46.0,61.175,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 95 | 0,26.0,20.575,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 96 | 0,59.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 97 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 98 | 0,71.0,34.6542,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 99 | 1,23.0,63.3583,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 100 | 1,34.0,23.0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 101 | 0,34.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 102 | 0,28.0,7.8958,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 103 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 104 | 0,21.0,77.2875,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 105 | 0,33.0,8.6542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 106 | 0,37.0,7.925,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 107 | 0,28.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 108 | 1,21.0,7.65,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 109 | 1,29.69911764705882,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 110 | 0,38.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 111 | 1,29.69911764705882,24.15,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 112 | 0,47.0,52.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 113 | 0,14.5,14.4542,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 114 | 0,22.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 115 | 0,20.0,9.825,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 116 | 0,17.0,14.4583,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 117 | 0,21.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 118 | 0,70.5,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 119 | 0,29.0,21.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 120 | 0,24.0,247.5208,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 121 | 0,2.0,31.275,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 122 | 0,21.0,73.5,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 123 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 124 | 0,32.5,30.0708,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 125 | 1,32.5,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 126 | 0,54.0,77.2875,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 127 | 1,12.0,11.2417,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 128 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 129 | 1,24.0,7.1417,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 130 | 1,29.69911764705882,22.3583,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 131 | 0,45.0,6.975,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 132 | 0,33.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 133 | 0,20.0,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 134 | 0,47.0,14.5,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 135 | 1,29.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 136 | 0,25.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 137 | 0,23.0,15.0458,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 138 | 1,19.0,26.2833,1,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 139 | 0,37.0,53.1,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 140 | 0,16.0,9.2167,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 141 | 0,24.0,79.2,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 142 | 0,29.69911764705882,15.2458,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 143 | 1,22.0,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 144 | 1,24.0,15.85,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 145 | 0,19.0,6.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 146 | 0,18.0,11.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 147 | 0,19.0,36.75,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 148 | 1,27.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 149 | 0,9.0,34.375,0,0,1,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1 150 | 0,36.5,26.0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 151 | 0,42.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 152 | 0,51.0,12.525,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 153 | 1,22.0,66.6,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 154 | 0,55.5,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 155 | 0,40.5,14.5,0,0,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 156 | 0,29.69911764705882,7.3125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 157 | 0,51.0,61.3792,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 158 | 1,16.0,7.7333,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 159 | 0,30.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 160 | 0,29.69911764705882,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 161 | 0,29.69911764705882,69.55,0,0,1,0,1,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1 162 | 0,44.0,16.1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 163 | 1,40.0,15.75,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 164 | 0,26.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 165 | 0,17.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 166 | 0,1.0,39.6875,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1 167 | 1,9.0,20.525,0,0,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 168 | 1,29.69911764705882,55.0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 169 | 0,45.0,27.9,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1 170 | 0,29.69911764705882,25.925,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 171 | 0,28.0,56.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 172 | 0,61.0,33.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 173 | 0,4.0,29.125,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0 174 | 1,1.0,11.1333,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 175 | 0,21.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 176 | 0,56.0,30.6958,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 177 | 0,18.0,7.8542,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 178 | 0,29.69911764705882,25.4667,0,0,1,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1 179 | 0,50.0,28.7125,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 180 | 0,30.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 181 | 0,36.0,0.0,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 182 | 0,29.69911764705882,69.55,0,0,1,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1 183 | 0,29.69911764705882,15.05,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 184 | 0,9.0,31.3875,0,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 185 | 1,1.0,39.0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1 186 | 1,4.0,22.025,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 187 | 0,29.69911764705882,50.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 188 | 1,29.69911764705882,15.5,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 189 | 1,45.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 190 | 0,40.0,15.5,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0 191 | 0,36.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 192 | 1,32.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 193 | 0,19.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 194 | 1,19.0,7.8542,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 195 | 1,3.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 196 | 1,44.0,27.7208,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 197 | 1,58.0,146.5208,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 198 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 199 | 0,42.0,8.4042,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 200 | 1,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 201 | 0,24.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 202 | 0,28.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 203 | 0,29.69911764705882,69.55,0,0,1,0,1,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1 204 | 0,34.0,6.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 205 | 0,45.5,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 206 | 1,18.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 207 | 0,2.0,10.4625,0,0,1,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 208 | 0,32.0,15.85,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 209 | 1,26.0,18.7875,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 210 | 1,16.0,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 211 | 1,40.0,31.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 212 | 0,24.0,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 213 | 1,35.0,21.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 214 | 0,22.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 215 | 0,30.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 216 | 0,29.69911764705882,7.75,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 217 | 1,31.0,113.275,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 218 | 1,27.0,7.925,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 219 | 0,42.0,27.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 220 | 1,32.0,76.2917,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 221 | 0,30.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 222 | 1,16.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 223 | 0,27.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 224 | 0,51.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 225 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 226 | 1,38.0,90.0,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 227 | 0,22.0,9.35,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 228 | 1,19.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 229 | 0,20.5,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 230 | 0,18.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 231 | 0,29.69911764705882,25.4667,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1 232 | 1,35.0,83.475,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 233 | 0,29.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 234 | 0,59.0,13.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 235 | 1,5.0,31.3875,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 236 | 0,24.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 237 | 0,29.69911764705882,7.55,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 238 | 0,44.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 239 | 1,8.0,26.25,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 240 | 0,19.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 241 | 0,33.0,12.275,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 242 | 0,29.69911764705882,14.4542,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 243 | 1,29.69911764705882,15.5,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 244 | 0,29.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 245 | 0,22.0,7.125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 246 | 0,30.0,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 247 | 0,44.0,90.0,1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1,0 248 | 0,25.0,7.775,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 249 | 1,24.0,14.5,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 250 | 1,37.0,52.5542,1,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 251 | 0,54.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 252 | 0,29.69911764705882,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 253 | 0,29.0,10.4625,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 254 | 0,62.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 255 | 0,30.0,16.1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 256 | 0,41.0,20.2125,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 257 | 1,29.0,15.2458,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 258 | 1,29.69911764705882,79.2,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 259 | 1,30.0,86.5,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 260 | 1,35.0,512.3292,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 261 | 1,50.0,26.0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 262 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 263 | 1,3.0,31.3875,0,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 264 | 0,52.0,79.65,1,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 265 | 0,40.0,0.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 266 | 0,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 267 | 0,36.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 268 | 0,16.0,39.6875,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1 269 | 1,25.0,7.775,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 270 | 1,58.0,153.4625,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 271 | 1,35.0,135.6333,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 272 | 0,29.69911764705882,31.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 273 | 1,25.0,0.0,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 274 | 1,41.0,19.5,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 275 | 0,37.0,29.7,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 276 | 1,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 277 | 1,63.0,77.9583,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 278 | 0,45.0,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 279 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 280 | 0,7.0,29.125,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0 281 | 1,35.0,20.25,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 282 | 0,65.0,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 283 | 0,28.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 284 | 0,16.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 285 | 1,19.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 286 | 0,29.69911764705882,26.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 287 | 0,33.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 288 | 1,30.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 289 | 0,22.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 290 | 1,42.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 291 | 1,22.0,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 292 | 1,26.0,78.85,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 293 | 1,19.0,91.0792,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 294 | 0,36.0,12.875,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 295 | 0,24.0,8.85,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 296 | 0,24.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 297 | 0,29.69911764705882,27.7208,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 298 | 0,23.5,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 299 | 0,2.0,151.55,1,0,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 300 | 1,29.69911764705882,30.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 301 | 1,50.0,247.5208,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 302 | 1,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 303 | 1,29.69911764705882,23.25,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1,0 304 | 0,19.0,0.0,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 305 | 1,29.69911764705882,12.35,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 306 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 307 | 1,0.92,151.55,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 308 | 1,29.69911764705882,110.8833,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 309 | 1,17.0,108.9,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 310 | 0,30.0,24.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 311 | 1,30.0,56.9292,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 312 | 1,24.0,83.1583,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 313 | 1,18.0,262.375,1,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0 314 | 0,26.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 315 | 0,28.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 316 | 0,43.0,26.25,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 317 | 1,26.0,7.8542,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 318 | 1,24.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 319 | 0,54.0,14.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 320 | 1,31.0,164.8667,1,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 321 | 1,40.0,134.5,1,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 322 | 0,22.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 323 | 0,27.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 324 | 1,30.0,12.35,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 325 | 1,22.0,29.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 326 | 0,29.69911764705882,69.55,0,0,1,0,1,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1 327 | 1,36.0,135.6333,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 328 | 0,61.0,6.2375,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 329 | 1,36.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 330 | 1,31.0,20.525,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 331 | 1,16.0,57.9792,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 332 | 1,29.69911764705882,23.25,0,0,1,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1,0 333 | 0,45.5,28.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 334 | 0,38.0,153.4625,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 335 | 0,16.0,18.0,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 336 | 1,29.69911764705882,133.65,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 337 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 338 | 0,29.0,66.6,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 339 | 1,41.0,134.5,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 340 | 1,45.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 341 | 0,45.0,35.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 342 | 1,2.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 343 | 1,24.0,263.0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 344 | 0,28.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 345 | 0,25.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 346 | 0,36.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 347 | 1,24.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 348 | 1,40.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 349 | 1,29.69911764705882,16.1,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 350 | 1,3.0,15.9,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 351 | 0,42.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 352 | 0,23.0,9.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 353 | 0,29.69911764705882,35.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 354 | 0,15.0,7.2292,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 355 | 0,25.0,17.8,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 356 | 0,29.69911764705882,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 357 | 0,28.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 358 | 1,22.0,55.0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 359 | 0,38.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 360 | 1,29.69911764705882,7.8792,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 361 | 1,29.69911764705882,7.8792,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 362 | 0,40.0,27.9,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1 363 | 0,29.0,27.7208,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 364 | 0,45.0,14.4542,0,0,1,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 365 | 0,35.0,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 366 | 0,29.69911764705882,15.5,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 367 | 0,30.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 368 | 1,60.0,75.25,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 369 | 1,29.69911764705882,7.2292,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 370 | 1,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 371 | 1,24.0,69.3,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 372 | 1,25.0,55.4417,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 373 | 0,18.0,6.4958,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 374 | 0,19.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 375 | 0,22.0,135.6333,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 376 | 0,3.0,21.075,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1 377 | 1,29.69911764705882,82.1708,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 378 | 1,22.0,7.25,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 379 | 0,27.0,211.5,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 380 | 0,20.0,4.0125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 381 | 0,19.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 382 | 1,42.0,227.525,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 383 | 1,1.0,15.7417,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 384 | 0,32.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 385 | 1,35.0,52.0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 386 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 387 | 0,18.0,73.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 388 | 0,1.0,46.9,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1 389 | 1,36.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 390 | 0,29.69911764705882,7.7292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 391 | 1,17.0,12.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 392 | 1,36.0,120.0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 393 | 1,21.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 394 | 0,28.0,7.925,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 395 | 1,23.0,113.275,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 396 | 1,24.0,16.7,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 397 | 0,22.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 398 | 0,31.0,7.8542,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 399 | 0,46.0,26.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 400 | 0,23.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 401 | 1,28.0,12.65,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 402 | 1,39.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 403 | 0,26.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 404 | 0,21.0,9.825,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 405 | 0,28.0,15.85,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 406 | 0,20.0,8.6625,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 407 | 0,34.0,21.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 408 | 0,51.0,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 409 | 1,3.0,18.75,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 410 | 0,21.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 411 | 0,29.69911764705882,25.4667,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1 412 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 413 | 0,29.69911764705882,6.8583,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 414 | 1,33.0,90.0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 415 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 416 | 1,44.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 417 | 0,29.69911764705882,8.05,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 418 | 1,34.0,32.5,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 419 | 1,18.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 420 | 0,30.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 421 | 0,10.0,24.15,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 422 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 423 | 0,21.0,7.7333,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 424 | 0,29.0,7.875,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 425 | 0,28.0,14.4,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 426 | 0,18.0,20.2125,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 427 | 0,29.69911764705882,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 428 | 1,28.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 429 | 1,19.0,26.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 430 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 431 | 1,32.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 432 | 1,28.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 433 | 1,29.69911764705882,16.1,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 434 | 1,42.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 435 | 0,17.0,7.125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 436 | 0,50.0,55.9,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 437 | 1,14.0,120.0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 438 | 0,21.0,34.375,0,0,1,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1 439 | 1,24.0,18.75,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1 440 | 0,64.0,263.0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1 441 | 0,31.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 442 | 1,45.0,26.25,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 443 | 0,20.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 444 | 0,25.0,7.775,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 445 | 1,28.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 446 | 1,29.69911764705882,8.1125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 447 | 1,4.0,81.8583,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 448 | 1,13.0,19.5,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 449 | 1,34.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 450 | 1,5.0,19.2583,0,0,1,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0 451 | 1,52.0,30.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 452 | 0,36.0,27.75,0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 453 | 0,29.69911764705882,19.9667,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 454 | 0,30.0,27.75,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 455 | 1,49.0,89.1042,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 456 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 457 | 1,29.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 458 | 0,65.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 459 | 1,29.69911764705882,51.8625,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 460 | 1,50.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 461 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 462 | 1,48.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 463 | 0,34.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 464 | 0,47.0,38.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 465 | 0,48.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 466 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 467 | 0,38.0,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 468 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 469 | 0,56.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 470 | 0,29.69911764705882,7.725,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 471 | 1,0.75,19.2583,0,0,1,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0 472 | 0,29.69911764705882,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 473 | 0,38.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 474 | 1,33.0,27.75,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 475 | 1,23.0,13.7917,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 476 | 0,22.0,9.8375,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 477 | 0,29.69911764705882,52.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 478 | 0,34.0,21.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 479 | 0,29.0,7.0458,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 480 | 0,22.0,7.5208,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 481 | 1,2.0,12.2875,0,0,1,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 482 | 0,9.0,46.9,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1 483 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 484 | 0,50.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 485 | 1,63.0,9.5875,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 486 | 1,25.0,91.0792,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 487 | 0,29.69911764705882,25.4667,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1 488 | 1,35.0,90.0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 489 | 0,58.0,29.7,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 490 | 0,30.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 491 | 1,9.0,15.9,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 492 | 0,29.69911764705882,19.9667,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 493 | 0,21.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 494 | 0,55.0,30.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 495 | 0,71.0,49.5042,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 496 | 0,21.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 497 | 0,29.69911764705882,14.4583,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 498 | 1,54.0,78.2667,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 499 | 0,29.69911764705882,15.1,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 500 | 0,25.0,151.55,1,0,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 501 | 0,24.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 502 | 0,17.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 503 | 0,21.0,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 504 | 0,29.69911764705882,7.6292,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 505 | 0,37.0,9.5875,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 506 | 1,16.0,86.5,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 507 | 0,18.0,108.9,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 508 | 1,33.0,26.0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 509 | 1,29.69911764705882,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 510 | 0,28.0,22.525,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 511 | 1,26.0,56.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 512 | 1,29.0,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 513 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 514 | 1,36.0,26.2875,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 515 | 1,54.0,59.4,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 516 | 0,24.0,7.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 517 | 0,47.0,34.0208,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 518 | 1,34.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 519 | 0,29.69911764705882,24.15,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 520 | 1,36.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 521 | 0,32.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 522 | 1,30.0,93.5,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 523 | 0,22.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 524 | 0,29.69911764705882,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 525 | 1,44.0,57.9792,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 526 | 0,29.69911764705882,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 527 | 0,40.5,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 528 | 1,50.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 529 | 0,29.69911764705882,221.7792,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 530 | 0,39.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 531 | 0,23.0,11.5,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1 532 | 1,2.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 533 | 0,29.69911764705882,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 534 | 0,17.0,7.2292,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 535 | 1,29.69911764705882,22.3583,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 536 | 0,30.0,8.6625,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 537 | 1,7.0,26.25,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 538 | 0,45.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 539 | 1,30.0,106.425,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 540 | 0,29.69911764705882,14.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 541 | 1,22.0,49.5,1,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 542 | 1,36.0,71.0,1,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 543 | 0,9.0,31.275,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 544 | 0,11.0,31.275,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 545 | 1,32.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 546 | 0,50.0,106.425,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 547 | 0,64.0,26.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 548 | 1,19.0,26.0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 549 | 1,29.69911764705882,13.8625,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 550 | 0,33.0,20.525,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 551 | 1,8.0,36.75,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 552 | 1,17.0,110.8833,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 553 | 0,27.0,26.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 554 | 0,29.69911764705882,7.8292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 555 | 1,22.0,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 556 | 1,22.0,7.775,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 557 | 0,62.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 558 | 1,48.0,39.6,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 559 | 0,29.69911764705882,227.525,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 560 | 1,39.0,79.65,1,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 561 | 1,36.0,17.4,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 562 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 563 | 0,40.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 564 | 0,28.0,13.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 565 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 566 | 0,29.69911764705882,8.05,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 567 | 0,24.0,24.15,0,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 568 | 0,19.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 569 | 0,29.0,21.075,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1 570 | 0,29.69911764705882,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 571 | 1,32.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 572 | 1,62.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 573 | 1,53.0,51.4792,1,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 574 | 1,36.0,26.3875,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 575 | 1,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 576 | 0,16.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 577 | 0,19.0,14.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 578 | 1,34.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 579 | 1,39.0,55.9,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 580 | 0,29.69911764705882,14.4583,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 581 | 1,32.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 582 | 1,25.0,30.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 583 | 1,39.0,110.8833,1,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 584 | 0,54.0,26.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 585 | 0,36.0,40.125,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 586 | 0,29.69911764705882,8.7125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 587 | 1,18.0,79.65,1,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 588 | 0,47.0,15.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 589 | 1,60.0,79.2,1,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 590 | 0,22.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 591 | 0,29.69911764705882,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 592 | 0,35.0,7.125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 593 | 1,52.0,78.2667,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 594 | 0,47.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 595 | 0,29.69911764705882,7.75,0,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0 596 | 0,37.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 597 | 0,36.0,24.15,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 598 | 1,29.69911764705882,33.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 599 | 0,49.0,0.0,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 600 | 0,29.69911764705882,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 601 | 1,49.0,56.9292,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 602 | 1,24.0,27.0,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1 603 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 604 | 0,29.69911764705882,42.4,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 605 | 0,44.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 606 | 1,35.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 607 | 0,36.0,15.55,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 608 | 0,30.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 609 | 1,27.0,30.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 610 | 1,22.0,41.5792,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 611 | 1,40.0,153.4625,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 612 | 0,39.0,31.275,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1 613 | 0,29.69911764705882,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 614 | 1,29.69911764705882,15.5,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 615 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 616 | 0,35.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 617 | 1,24.0,65.0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 618 | 0,34.0,14.4,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 619 | 0,26.0,16.1,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 620 | 1,4.0,39.0,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1 621 | 0,26.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 622 | 0,27.0,14.4542,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 623 | 1,42.0,52.5542,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 624 | 1,20.0,15.7417,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 625 | 0,21.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 626 | 0,21.0,16.1,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 627 | 0,61.0,32.3208,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 628 | 0,57.0,12.35,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 629 | 1,21.0,77.9583,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 630 | 0,26.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 631 | 0,29.69911764705882,7.7333,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 632 | 1,80.0,30.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 633 | 0,51.0,7.0542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 634 | 1,32.0,30.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 635 | 0,29.69911764705882,0.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 636 | 0,9.0,27.9,0,0,1,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 637 | 1,28.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 638 | 0,32.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 639 | 0,31.0,26.25,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 640 | 0,41.0,39.6875,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1 641 | 0,29.69911764705882,16.1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 642 | 0,20.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 643 | 1,24.0,69.3,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 644 | 0,2.0,27.9,0,0,1,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 645 | 1,29.69911764705882,56.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 646 | 1,0.75,19.2583,0,0,1,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0 647 | 1,48.0,76.7292,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 648 | 0,19.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 649 | 1,56.0,35.5,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 650 | 0,29.69911764705882,7.55,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 651 | 1,23.0,7.55,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 652 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 653 | 1,18.0,23.0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 654 | 0,21.0,8.4333,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 655 | 1,29.69911764705882,7.8292,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 656 | 0,18.0,6.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 657 | 0,24.0,73.5,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 658 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 659 | 0,32.0,15.5,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0 660 | 0,23.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 661 | 0,58.0,113.275,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 662 | 1,50.0,133.65,1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 663 | 0,40.0,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 664 | 0,47.0,25.5875,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 665 | 0,36.0,7.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 666 | 1,20.0,7.925,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 667 | 0,32.0,73.5,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1 668 | 0,25.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 669 | 0,29.69911764705882,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 670 | 0,43.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 671 | 1,29.69911764705882,52.0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 672 | 1,40.0,39.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 673 | 0,31.0,52.0,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 674 | 0,70.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 675 | 1,31.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 676 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 677 | 0,18.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 678 | 0,24.5,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 679 | 1,18.0,9.8417,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 680 | 0,43.0,46.9,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1 681 | 1,36.0,512.3292,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 682 | 0,29.69911764705882,8.1375,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 683 | 1,27.0,76.7292,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 684 | 0,20.0,9.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 685 | 0,14.0,46.9,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1 686 | 0,60.0,39.0,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 687 | 0,25.0,41.5792,0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0 688 | 0,14.0,39.6875,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1 689 | 0,19.0,10.1708,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 690 | 0,18.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 691 | 1,15.0,211.3375,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 692 | 1,31.0,57.0,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 693 | 1,4.0,13.4167,0,0,1,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 694 | 1,29.69911764705882,56.4958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 695 | 0,25.0,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 696 | 0,60.0,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 697 | 0,52.0,13.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 698 | 0,44.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 699 | 1,29.69911764705882,7.7333,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 700 | 0,49.0,110.8833,1,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 701 | 0,42.0,7.65,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 702 | 1,18.0,227.525,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 703 | 1,35.0,26.2875,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 704 | 0,18.0,14.4542,0,0,1,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 705 | 0,25.0,7.7417,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 706 | 0,26.0,7.8542,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 707 | 0,39.0,26.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 708 | 1,45.0,13.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 709 | 1,42.0,26.2875,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 710 | 1,22.0,151.55,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 711 | 1,29.69911764705882,15.2458,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 712 | 1,24.0,49.5042,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 713 | 0,29.69911764705882,26.55,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 714 | 1,48.0,52.0,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 715 | 0,29.0,9.4833,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 716 | 0,52.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 717 | 0,19.0,7.65,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 718 | 1,38.0,227.525,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 719 | 1,27.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 720 | 0,29.69911764705882,15.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 721 | 0,33.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 722 | 1,6.0,33.0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 723 | 0,17.0,7.0542,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 724 | 0,34.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 725 | 0,50.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 726 | 1,27.0,53.1,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 727 | 0,20.0,8.6625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 728 | 1,30.0,21.0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1 729 | 1,29.69911764705882,7.7375,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 730 | 0,25.0,26.0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 731 | 0,25.0,7.925,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 732 | 1,29.0,211.3375,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 733 | 0,11.0,18.7875,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 734 | 0,29.69911764705882,0.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 735 | 0,23.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 736 | 0,23.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 737 | 0,28.5,16.1,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 738 | 0,48.0,34.375,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1 739 | 1,35.0,512.3292,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 740 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 741 | 0,29.69911764705882,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 742 | 1,29.69911764705882,30.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 743 | 0,36.0,78.85,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 744 | 1,21.0,262.375,1,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0 745 | 0,24.0,16.1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 746 | 1,31.0,7.925,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 747 | 0,70.0,71.0,1,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 748 | 0,16.0,20.25,0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 749 | 1,30.0,13.0,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 750 | 0,19.0,53.1,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 751 | 0,31.0,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 752 | 1,4.0,23.0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 753 | 1,6.0,12.475,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 754 | 0,33.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 755 | 0,23.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 756 | 1,48.0,65.0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 757 | 1,0.67,14.5,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 758 | 0,28.0,7.7958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 759 | 0,18.0,11.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 760 | 0,34.0,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 761 | 1,33.0,86.5,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 762 | 0,29.69911764705882,14.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 763 | 0,41.0,7.125,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 764 | 1,20.0,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 765 | 1,36.0,120.0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 766 | 0,16.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 767 | 1,51.0,77.9583,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 768 | 0,29.69911764705882,39.6,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 769 | 0,30.5,7.75,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 770 | 0,29.69911764705882,24.15,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 771 | 0,32.0,8.3625,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 772 | 0,24.0,9.5,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 773 | 0,48.0,7.8542,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 774 | 0,57.0,10.5,0,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 775 | 0,29.69911764705882,7.225,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 776 | 1,54.0,23.0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1 777 | 0,18.0,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 778 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 779 | 1,5.0,12.475,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 780 | 0,29.69911764705882,7.7375,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 781 | 1,43.0,211.3375,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 782 | 1,13.0,7.2292,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 783 | 1,17.0,57.0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 784 | 0,29.0,30.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 785 | 0,29.69911764705882,23.45,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 786 | 0,25.0,7.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 787 | 0,25.0,7.25,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 788 | 1,18.0,7.4958,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 789 | 0,8.0,29.125,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0 790 | 1,1.0,20.575,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 791 | 0,46.0,79.2,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 792 | 0,29.69911764705882,7.75,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0 793 | 0,16.0,26.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 794 | 0,29.69911764705882,69.55,0,0,1,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1 795 | 0,29.69911764705882,30.6958,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 796 | 0,25.0,7.8958,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 797 | 0,39.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 798 | 1,49.0,25.9292,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 799 | 1,31.0,8.6833,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 800 | 0,30.0,7.2292,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0 801 | 0,30.0,24.15,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 802 | 0,34.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 803 | 1,31.0,26.25,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 804 | 1,11.0,120.0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1 805 | 1,0.42,8.5167,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 806 | 1,27.0,6.975,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 807 | 0,31.0,7.775,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 808 | 0,39.0,0.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 809 | 0,18.0,7.775,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 810 | 0,39.0,13.0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 811 | 1,33.0,53.1,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 812 | 0,26.0,7.8875,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 813 | 0,39.0,24.15,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 814 | 0,35.0,10.5,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 815 | 0,6.0,31.275,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1 816 | 0,30.5,8.05,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 817 | 0,29.69911764705882,0.0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 818 | 0,23.0,7.925,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 819 | 0,31.0,37.0042,0,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 820 | 0,43.0,6.45,0,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1 821 | 0,10.0,27.9,0,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1 822 | 1,52.0,93.5,1,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 823 | 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| LP002980,N 367 | LP002986,N 368 | LP002989,N -------------------------------------------------------------------------------- /Loan Prediction/Datasets/test_lAUu6dG.csv: -------------------------------------------------------------------------------- 1 | Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area 2 | LP001015,Male,Yes,0,Graduate,No,5720,0,110,360,1,Urban 3 | LP001022,Male,Yes,1,Graduate,No,3076,1500,126,360,1,Urban 4 | LP001031,Male,Yes,2,Graduate,No,5000,1800,208,360,1,Urban 5 | LP001035,Male,Yes,2,Graduate,No,2340,2546,100,360,,Urban 6 | LP001051,Male,No,0,Not Graduate,No,3276,0,78,360,1,Urban 7 | LP001054,Male,Yes,0,Not Graduate,Yes,2165,3422,152,360,1,Urban 8 | LP001055,Female,No,1,Not Graduate,No,2226,0,59,360,1,Semiurban 9 | LP001056,Male,Yes,2,Not Graduate,No,3881,0,147,360,0,Rural 10 | LP001059,Male,Yes,2,Graduate,,13633,0,280,240,1,Urban 11 | LP001067,Male,No,0,Not Graduate,No,2400,2400,123,360,1,Semiurban 12 | LP001078,Male,No,0,Not Graduate,No,3091,0,90,360,1,Urban 13 | LP001082,Male,Yes,1,Graduate,,2185,1516,162,360,1,Semiurban 14 | LP001083,Male,No,3+,Graduate,No,4166,0,40,180,,Urban 15 | LP001094,Male,Yes,2,Graduate,,12173,0,166,360,0,Semiurban 16 | LP001096,Female,No,0,Graduate,No,4666,0,124,360,1,Semiurban 17 | LP001099,Male,No,1,Graduate,No,5667,0,131,360,1,Urban 18 | LP001105,Male,Yes,2,Graduate,No,4583,2916,200,360,1,Urban 19 | LP001107,Male,Yes,3+,Graduate,No,3786,333,126,360,1,Semiurban 20 | LP001108,Male,Yes,0,Graduate,No,9226,7916,300,360,1,Urban 21 | LP001115,Male,No,0,Graduate,No,1300,3470,100,180,1,Semiurban 22 | LP001121,Male,Yes,1,Not Graduate,No,1888,1620,48,360,1,Urban 23 | LP001124,Female,No,3+,Not Graduate,No,2083,0,28,180,1,Urban 24 | LP001128,,No,0,Graduate,No,3909,0,101,360,1,Urban 25 | LP001135,Female,No,0,Not Graduate,No,3765,0,125,360,1,Urban 26 | LP001149,Male,Yes,0,Graduate,No,5400,4380,290,360,1,Urban 27 | LP001153,Male,No,0,Graduate,No,0,24000,148,360,0,Rural 28 | LP001163,Male,Yes,2,Graduate,No,4363,1250,140,360,,Urban 29 | LP001169,Male,Yes,0,Graduate,No,7500,3750,275,360,1,Urban 30 | LP001174,Male,Yes,0,Graduate,No,3772,833,57,360,,Semiurban 31 | LP001176,Male,No,0,Graduate,No,2942,2382,125,180,1,Urban 32 | LP001177,Female,No,0,Not Graduate,No,2478,0,75,360,1,Semiurban 33 | LP001183,Male,Yes,2,Graduate,No,6250,820,192,360,1,Urban 34 | LP001185,Male,No,0,Graduate,No,3268,1683,152,360,1,Semiurban 35 | LP001187,Male,Yes,0,Graduate,No,2783,2708,158,360,1,Urban 36 | LP001190,Male,Yes,0,Graduate,No,2740,1541,101,360,1,Urban 37 | LP001203,Male,No,0,Graduate,No,3150,0,176,360,0,Semiurban 38 | LP001208,Male,Yes,2,Graduate,,7350,4029,185,180,1,Urban 39 | LP001210,Male,Yes,0,Graduate,Yes,2267,2792,90,360,1,Urban 40 | LP001211,Male,No,0,Graduate,Yes,5833,0,116,360,1,Urban 41 | LP001219,Male,No,0,Graduate,No,3643,1963,138,360,1,Urban 42 | LP001220,Male,Yes,0,Graduate,No,5629,818,100,360,1,Urban 43 | LP001221,Female,No,0,Graduate,No,3644,0,110,360,1,Urban 44 | LP001226,Male,Yes,0,Not Graduate,No,1750,2024,90,360,1,Semiurban 45 | LP001230,Male,No,0,Graduate,No,6500,2600,200,360,1,Semiurban 46 | LP001231,Female,No,0,Graduate,No,3666,0,84,360,1,Urban 47 | LP001232,Male,Yes,0,Graduate,No,4260,3900,185,,,Urban 48 | LP001237,Male,Yes,,Not Graduate,No,4163,1475,162,360,1,Urban 49 | LP001242,Male,No,0,Not Graduate,No,2356,1902,108,360,1,Semiurban 50 | LP001268,Male,No,0,Graduate,No,6792,3338,187,,1,Urban 51 | LP001270,Male,Yes,3+,Not Graduate,Yes,8000,250,187,360,1,Semiurban 52 | LP001284,Male,Yes,1,Graduate,No,2419,1707,124,360,1,Urban 53 | LP001287,,Yes,3+,Not Graduate,No,3500,833,120,360,1,Semiurban 54 | LP001291,Male,Yes,1,Graduate,No,3500,3077,160,360,1,Semiurban 55 | LP001298,Male,Yes,2,Graduate,No,4116,1000,30,180,1,Urban 56 | LP001312,Male,Yes,0,Not Graduate,Yes,5293,0,92,360,1,Urban 57 | LP001313,Male,No,0,Graduate,No,2750,0,130,360,0,Urban 58 | LP001317,Female,No,0,Not Graduate,No,4402,0,130,360,1,Rural 59 | LP001321,Male,Yes,2,Graduate,No,3613,3539,134,180,1,Semiurban 60 | LP001323,Female,Yes,2,Graduate,No,2779,3664,176,360,0,Semiurban 61 | LP001324,Male,Yes,3+,Graduate,No,4720,0,90,180,1,Semiurban 62 | LP001332,Male,Yes,0,Not Graduate,No,2415,1721,110,360,1,Semiurban 63 | LP001335,Male,Yes,0,Graduate,Yes,7016,292,125,360,1,Urban 64 | LP001338,Female,No,2,Graduate,No,4968,0,189,360,1,Semiurban 65 | LP001347,Female,No,0,Graduate,No,2101,1500,108,360,0,Rural 66 | LP001348,Male,Yes,3+,Not Graduate,No,4490,0,125,360,1,Urban 67 | LP001351,Male,Yes,0,Graduate,No,2917,3583,138,360,1,Semiurban 68 | LP001352,Male,Yes,0,Not Graduate,No,4700,0,135,360,0,Semiurban 69 | LP001358,Male,Yes,0,Graduate,No,3445,0,130,360,0,Semiurban 70 | LP001359,Male,Yes,0,Graduate,No,7666,0,187,360,1,Semiurban 71 | LP001361,Male,Yes,0,Graduate,No,2458,5105,188,360,0,Rural 72 | LP001366,Female,No,,Graduate,No,3250,0,95,360,1,Semiurban 73 | LP001368,Male,No,0,Graduate,No,4463,0,65,360,1,Semiurban 74 | LP001375,Male,Yes,1,Graduate,,4083,1775,139,60,1,Urban 75 | LP001380,Male,Yes,0,Graduate,Yes,3900,2094,232,360,1,Rural 76 | LP001386,Male,Yes,0,Not Graduate,No,4750,3583,144,360,1,Semiurban 77 | LP001400,Male,No,0,Graduate,No,3583,3435,155,360,1,Urban 78 | LP001407,Male,Yes,0,Graduate,No,3189,2367,186,360,1,Urban 79 | LP001413,Male,No,0,Graduate,Yes,6356,0,50,360,1,Rural 80 | LP001415,Male,Yes,1,Graduate,No,3413,4053,,360,1,Semiurban 81 | LP001419,Female,Yes,0,Graduate,No,7950,0,185,360,1,Urban 82 | LP001420,Male,Yes,3+,Graduate,No,3829,1103,163,360,0,Urban 83 | LP001428,Male,Yes,3+,Graduate,No,72529,0,360,360,1,Urban 84 | LP001445,Male,Yes,2,Not Graduate,No,4136,0,149,480,0,Rural 85 | LP001446,Male,Yes,0,Graduate,No,8449,0,257,360,1,Rural 86 | LP001450,Male,Yes,0,Graduate,No,4456,0,131,180,0,Semiurban 87 | LP001452,Male,Yes,2,Graduate,No,4635,8000,102,180,1,Rural 88 | LP001455,Male,Yes,0,Graduate,No,3571,1917,135,360,1,Urban 89 | LP001466,Male,No,0,Graduate,No,3066,0,95,360,1,Semiurban 90 | LP001471,Male,No,2,Not Graduate,No,3235,2015,77,360,1,Semiurban 91 | LP001472,Female,No,0,Graduate,,5058,0,200,360,1,Rural 92 | LP001475,Male,Yes,0,Graduate,Yes,3188,2286,130,360,,Rural 93 | LP001483,Male,Yes,3+,Graduate,No,13518,0,390,360,1,Rural 94 | LP001486,Male,Yes,1,Graduate,No,4364,2500,185,360,1,Semiurban 95 | LP001490,Male,Yes,2,Not Graduate,No,4766,1646,100,360,1,Semiurban 96 | LP001496,Male,Yes,1,Graduate,No,4609,2333,123,360,0,Semiurban 97 | LP001499,Female,Yes,3+,Graduate,No,6260,0,110,360,1,Semiurban 98 | LP001500,Male,Yes,1,Graduate,No,3333,4200,256,360,1,Urban 99 | LP001501,Male,Yes,0,Graduate,No,3500,3250,140,360,1,Semiurban 100 | LP001517,Male,Yes,3+,Graduate,No,9719,0,61,360,1,Urban 101 | LP001527,Male,Yes,3+,Graduate,No,6835,0,188,360,,Semiurban 102 | LP001534,Male,No,0,Graduate,No,4452,0,131,360,1,Rural 103 | LP001542,Female,Yes,0,Graduate,No,2262,0,,480,0,Semiurban 104 | LP001547,Male,Yes,1,Graduate,No,3901,0,116,360,1,Urban 105 | LP001548,Male,Yes,2,Not Graduate,No,2687,0,50,180,1,Rural 106 | LP001558,Male,No,0,Graduate,No,2243,2233,107,360,,Semiurban 107 | LP001561,Female,Yes,0,Graduate,No,3417,1287,200,360,1,Semiurban 108 | LP001563,,No,0,Graduate,No,1596,1760,119,360,0,Urban 109 | LP001567,Male,Yes,3+,Graduate,No,4513,0,120,360,1,Rural 110 | LP001568,Male,Yes,0,Graduate,No,4500,0,140,360,1,Semiurban 111 | LP001573,Male,Yes,0,Not Graduate,No,4523,1350,165,360,1,Urban 112 | LP001584,Female,No,0,Graduate,Yes,4742,0,108,360,1,Semiurban 113 | LP001587,Male,Yes,,Graduate,No,4082,0,93,360,1,Semiurban 114 | LP001589,Female,No,0,Graduate,No,3417,0,102,360,1,Urban 115 | LP001591,Female,Yes,2,Graduate,No,2922,3396,122,360,1,Semiurban 116 | LP001599,Male,Yes,0,Graduate,No,4167,4754,160,360,1,Rural 117 | LP001601,Male,No,3+,Graduate,No,4243,4123,157,360,,Semiurban 118 | LP001607,Female,No,0,Not Graduate,No,0,1760,180,360,1,Semiurban 119 | LP001611,Male,Yes,1,Graduate,No,1516,2900,80,,0,Rural 120 | LP001613,Female,No,0,Graduate,No,1762,2666,104,360,0,Urban 121 | LP001622,Male,Yes,2,Graduate,No,724,3510,213,360,0,Rural 122 | LP001627,Male,No,0,Graduate,No,3125,0,65,360,1,Urban 123 | LP001650,Male,Yes,0,Graduate,No,2333,3803,146,360,1,Rural 124 | LP001651,Male,Yes,3+,Graduate,No,3350,1560,135,360,1,Urban 125 | LP001652,Male,No,0,Graduate,No,2500,6414,187,360,0,Rural 126 | LP001655,Female,No,0,Graduate,No,12500,0,300,360,0,Urban 127 | LP001660,Male,No,0,Graduate,No,4667,0,120,360,1,Semiurban 128 | LP001662,Male,No,0,Graduate,No,6500,0,71,360,0,Urban 129 | LP001663,Male,Yes,2,Graduate,No,7500,0,225,360,1,Urban 130 | LP001667,Male,No,0,Graduate,No,3073,0,70,180,1,Urban 131 | LP001695,Male,Yes,1,Not Graduate,No,3321,2088,70,,1,Semiurban 132 | LP001703,Male,Yes,0,Graduate,No,3333,1270,124,360,1,Urban 133 | LP001718,Male,No,0,Graduate,No,3391,0,132,360,1,Rural 134 | LP001728,Male,Yes,1,Graduate,Yes,3343,1517,105,360,1,Rural 135 | LP001735,Female,No,1,Graduate,No,3620,0,90,360,1,Urban 136 | LP001737,Male,No,0,Graduate,No,4000,0,83,84,1,Urban 137 | LP001739,Male,Yes,0,Graduate,No,4258,0,125,360,1,Urban 138 | LP001742,Male,Yes,2,Graduate,No,4500,0,147,360,1,Rural 139 | LP001757,Male,Yes,1,Graduate,No,2014,2925,120,360,1,Rural 140 | LP001769,,No,,Graduate,No,3333,1250,110,360,1,Semiurban 141 | LP001771,Female,No,3+,Graduate,No,4083,0,103,360,,Semiurban 142 | LP001785,Male,No,0,Graduate,No,4727,0,150,360,0,Rural 143 | LP001787,Male,Yes,3+,Graduate,No,3089,2999,100,240,1,Rural 144 | LP001789,Male,Yes,3+,Not Graduate,,6794,528,139,360,0,Urban 145 | LP001791,Male,Yes,0,Graduate,Yes,32000,0,550,360,,Semiurban 146 | LP001794,Male,Yes,2,Graduate,Yes,10890,0,260,12,1,Rural 147 | LP001797,Female,No,0,Graduate,No,12941,0,150,300,1,Urban 148 | LP001815,Male,No,0,Not Graduate,No,3276,0,90,360,1,Semiurban 149 | LP001817,Male,No,0,Not Graduate,Yes,8703,0,199,360,0,Rural 150 | LP001818,Male,Yes,1,Graduate,No,4742,717,139,360,1,Semiurban 151 | LP001822,Male,No,0,Graduate,No,5900,0,150,360,1,Urban 152 | LP001827,Male,No,0,Graduate,No,3071,4309,180,360,1,Urban 153 | LP001831,Male,Yes,0,Graduate,No,2783,1456,113,360,1,Urban 154 | LP001842,Male,No,0,Graduate,No,5000,0,148,360,1,Rural 155 | LP001853,Male,Yes,1,Not Graduate,No,2463,2360,117,360,0,Urban 156 | LP001855,Male,Yes,2,Graduate,No,4855,0,72,360,1,Rural 157 | LP001857,Male,No,0,Not Graduate,Yes,1599,2474,125,300,1,Semiurban 158 | LP001862,Male,Yes,2,Graduate,Yes,4246,4246,214,360,1,Urban 159 | LP001867,Male,Yes,0,Graduate,No,4333,2291,133,350,1,Rural 160 | LP001878,Male,No,1,Graduate,No,5823,2529,187,360,1,Semiurban 161 | LP001881,Male,Yes,0,Not Graduate,No,7895,0,143,360,1,Rural 162 | LP001886,Male,No,0,Graduate,No,4150,4256,209,360,1,Rural 163 | LP001906,Male,No,0,Graduate,,2964,0,84,360,0,Semiurban 164 | LP001909,Male,No,0,Graduate,No,5583,0,116,360,1,Urban 165 | LP001911,Female,No,0,Graduate,No,2708,0,65,360,1,Rural 166 | LP001921,Male,No,1,Graduate,No,3180,2370,80,240,,Rural 167 | LP001923,Male,No,0,Not Graduate,No,2268,0,170,360,0,Semiurban 168 | LP001933,Male,No,2,Not Graduate,No,1141,2017,120,360,0,Urban 169 | LP001943,Male,Yes,0,Graduate,No,3042,3167,135,360,1,Urban 170 | LP001950,Female,Yes,3+,Graduate,,1750,2935,94,360,0,Semiurban 171 | LP001959,Female,Yes,1,Graduate,No,3564,0,79,360,1,Rural 172 | LP001961,Female,No,0,Graduate,No,3958,0,110,360,1,Rural 173 | LP001973,Male,Yes,2,Not Graduate,No,4483,0,130,360,1,Rural 174 | LP001975,Male,Yes,0,Graduate,No,5225,0,143,360,1,Rural 175 | LP001979,Male,No,0,Graduate,No,3017,2845,159,180,0,Urban 176 | LP001995,Male,Yes,0,Not Graduate,No,2431,1820,110,360,0,Rural 177 | LP001999,Male,Yes,2,Graduate,,4912,4614,160,360,1,Rural 178 | LP002007,Male,Yes,2,Not Graduate,No,2500,3333,131,360,1,Urban 179 | LP002009,Female,No,0,Graduate,No,2918,0,65,360,,Rural 180 | LP002016,Male,Yes,2,Graduate,No,5128,0,143,360,1,Rural 181 | LP002017,Male,Yes,3+,Graduate,No,15312,0,187,360,,Urban 182 | LP002018,Male,Yes,2,Graduate,No,3958,2632,160,360,1,Semiurban 183 | LP002027,Male,Yes,0,Graduate,No,4334,2945,165,360,1,Semiurban 184 | LP002028,Male,Yes,2,Graduate,No,4358,0,110,360,1,Urban 185 | LP002042,Female,Yes,1,Graduate,No,4000,3917,173,360,1,Rural 186 | LP002045,Male,Yes,3+,Graduate,No,10166,750,150,,1,Urban 187 | LP002046,Male,Yes,0,Not Graduate,No,4483,0,135,360,,Semiurban 188 | LP002047,Male,Yes,2,Not Graduate,No,4521,1184,150,360,1,Semiurban 189 | LP002056,Male,Yes,2,Graduate,No,9167,0,235,360,1,Semiurban 190 | LP002057,Male,Yes,0,Not Graduate,No,13083,0,,360,1,Rural 191 | LP002059,Male,Yes,2,Graduate,No,7874,3967,336,360,1,Rural 192 | LP002062,Female,Yes,1,Graduate,No,4333,0,132,84,1,Rural 193 | LP002064,Male,No,0,Graduate,No,4083,0,96,360,1,Urban 194 | LP002069,Male,Yes,2,Not Graduate,,3785,2912,180,360,0,Rural 195 | LP002070,Male,Yes,3+,Not Graduate,No,2654,1998,128,360,0,Rural 196 | LP002077,Male,Yes,1,Graduate,No,10000,2690,412,360,1,Semiurban 197 | LP002083,Male,No,0,Graduate,Yes,5833,0,116,360,1,Urban 198 | LP002090,Male,Yes,1,Graduate,No,4796,0,114,360,0,Semiurban 199 | LP002096,Male,Yes,0,Not Graduate,No,2000,1600,115,360,1,Rural 200 | LP002099,Male,Yes,2,Graduate,No,2540,700,104,360,0,Urban 201 | LP002102,Male,Yes,0,Graduate,Yes,1900,1442,88,360,1,Rural 202 | LP002105,Male,Yes,0,Graduate,Yes,8706,0,108,480,1,Rural 203 | LP002107,Male,Yes,3+,Not Graduate,No,2855,542,90,360,1,Urban 204 | LP002111,Male,Yes,,Graduate,No,3016,1300,100,360,,Urban 205 | LP002117,Female,Yes,0,Graduate,No,3159,2374,108,360,1,Semiurban 206 | LP002118,Female,No,0,Graduate,No,1937,1152,78,360,1,Semiurban 207 | LP002123,Male,Yes,0,Graduate,No,2613,2417,123,360,1,Semiurban 208 | LP002125,Male,Yes,1,Graduate,No,4960,2600,187,360,1,Semiurban 209 | LP002148,Male,Yes,1,Graduate,No,3074,1083,146,360,1,Semiurban 210 | LP002152,Female,No,0,Graduate,No,4213,0,80,360,1,Urban 211 | LP002165,,No,1,Not Graduate,No,2038,4027,100,360,1,Rural 212 | LP002167,Female,No,0,Graduate,No,2362,0,55,360,1,Urban 213 | LP002168,Male,No,0,Graduate,No,5333,2400,200,360,0,Rural 214 | LP002172,Male,Yes,3+,Graduate,Yes,5384,0,150,360,1,Semiurban 215 | LP002176,Male,No,0,Graduate,No,5708,0,150,360,1,Rural 216 | LP002183,Male,Yes,0,Not Graduate,No,3754,3719,118,,1,Rural 217 | LP002184,Male,Yes,0,Not Graduate,No,2914,2130,150,300,1,Urban 218 | LP002186,Male,Yes,0,Not Graduate,No,2747,2458,118,36,1,Semiurban 219 | LP002192,Male,Yes,0,Graduate,No,7830,2183,212,360,1,Rural 220 | LP002195,Male,Yes,1,Graduate,Yes,3507,3148,212,360,1,Rural 221 | LP002208,Male,Yes,1,Graduate,No,3747,2139,125,360,1,Urban 222 | LP002212,Male,Yes,0,Graduate,No,2166,2166,108,360,,Urban 223 | LP002240,Male,Yes,0,Not Graduate,No,3500,2168,149,360,1,Rural 224 | LP002245,Male,Yes,2,Not Graduate,No,2896,0,80,480,1,Urban 225 | LP002253,Female,No,1,Graduate,No,5062,0,152,300,1,Rural 226 | LP002256,Female,No,2,Graduate,Yes,5184,0,187,360,0,Semiurban 227 | LP002257,Female,No,0,Graduate,No,2545,0,74,360,1,Urban 228 | LP002264,Male,Yes,0,Graduate,No,2553,1768,102,360,1,Urban 229 | LP002270,Male,Yes,1,Graduate,No,3436,3809,100,360,1,Rural 230 | LP002279,Male,No,0,Graduate,No,2412,2755,130,360,1,Rural 231 | LP002286,Male,Yes,3+,Not Graduate,No,5180,0,125,360,0,Urban 232 | LP002294,Male,No,0,Graduate,No,14911,14507,130,360,1,Semiurban 233 | LP002298,,No,0,Graduate,Yes,2860,2988,138,360,1,Urban 234 | LP002306,Male,Yes,0,Graduate,No,1173,1594,28,180,1,Rural 235 | LP002310,Female,No,1,Graduate,No,7600,0,92,360,1,Semiurban 236 | LP002311,Female,Yes,0,Graduate,No,2157,1788,104,360,1,Urban 237 | LP002316,Male,No,0,Graduate,No,2231,2774,176,360,0,Urban 238 | LP002321,Female,No,0,Graduate,No,2274,5211,117,360,0,Semiurban 239 | LP002325,Male,Yes,2,Not Graduate,No,6166,13983,102,360,1,Rural 240 | LP002326,Male,Yes,2,Not Graduate,No,2513,1110,107,360,1,Semiurban 241 | LP002329,Male,No,0,Graduate,No,4333,0,66,480,1,Urban 242 | LP002333,Male,No,0,Not Graduate,No,3844,0,105,360,1,Urban 243 | LP002339,Male,Yes,0,Graduate,No,3887,1517,105,360,0,Semiurban 244 | LP002344,Male,Yes,0,Graduate,No,3510,828,105,360,1,Semiurban 245 | LP002346,Male,Yes,0,Graduate,,2539,1704,125,360,0,Rural 246 | LP002354,Female,No,0,Not Graduate,No,2107,0,64,360,1,Semiurban 247 | LP002355,,Yes,0,Graduate,No,3186,3145,150,180,0,Semiurban 248 | LP002358,Male,Yes,2,Graduate,Yes,5000,2166,150,360,1,Urban 249 | LP002360,Male,Yes,,Graduate,No,10000,0,,360,1,Urban 250 | LP002375,Male,Yes,0,Not Graduate,Yes,3943,0,64,360,1,Semiurban 251 | LP002376,Male,No,0,Graduate,No,2925,0,40,180,1,Rural 252 | LP002383,Male,Yes,3+,Graduate,No,3242,437,142,480,0,Urban 253 | LP002385,Male,Yes,,Graduate,No,3863,0,70,300,1,Semiurban 254 | LP002389,Female,No,1,Graduate,No,4028,0,131,360,1,Semiurban 255 | LP002394,Male,Yes,2,Graduate,No,4010,1025,120,360,1,Urban 256 | LP002397,Female,Yes,1,Graduate,No,3719,1585,114,360,1,Urban 257 | LP002399,Male,No,0,Graduate,,2858,0,123,360,0,Rural 258 | LP002400,Female,Yes,0,Graduate,No,3833,0,92,360,1,Rural 259 | LP002402,Male,Yes,0,Graduate,No,3333,4288,160,360,1,Urban 260 | LP002412,Male,Yes,0,Graduate,No,3007,3725,151,360,1,Rural 261 | LP002415,Female,No,1,Graduate,,1850,4583,81,360,,Rural 262 | LP002417,Male,Yes,3+,Not Graduate,No,2792,2619,171,360,1,Semiurban 263 | LP002420,Male,Yes,0,Graduate,No,2982,1550,110,360,1,Semiurban 264 | LP002425,Male,No,0,Graduate,No,3417,738,100,360,,Rural 265 | LP002433,Male,Yes,1,Graduate,No,18840,0,234,360,1,Rural 266 | LP002440,Male,Yes,2,Graduate,No,2995,1120,184,360,1,Rural 267 | LP002441,Male,No,,Graduate,No,3579,3308,138,360,,Semiurban 268 | LP002442,Female,Yes,1,Not Graduate,No,3835,1400,112,480,0,Urban 269 | LP002445,Female,No,1,Not Graduate,No,3854,3575,117,360,1,Rural 270 | LP002450,Male,Yes,2,Graduate,No,5833,750,49,360,0,Rural 271 | LP002471,Male,No,0,Graduate,No,3508,0,99,360,1,Rural 272 | LP002476,Female,Yes,3+,Not Graduate,No,1635,2444,99,360,1,Urban 273 | LP002482,Female,No,0,Graduate,Yes,3333,3916,212,360,1,Rural 274 | LP002485,Male,No,1,Graduate,No,24797,0,240,360,1,Semiurban 275 | LP002495,Male,Yes,2,Graduate,No,5667,440,130,360,0,Semiurban 276 | LP002496,Female,No,0,Graduate,No,3500,0,94,360,0,Semiurban 277 | LP002523,Male,Yes,3+,Graduate,No,2773,1497,108,360,1,Semiurban 278 | LP002542,Male,Yes,0,Graduate,,6500,0,144,360,1,Urban 279 | LP002550,Female,No,0,Graduate,No,5769,0,110,180,1,Semiurban 280 | LP002551,Male,Yes,3+,Not Graduate,,3634,910,176,360,0,Semiurban 281 | LP002553,,No,0,Graduate,No,29167,0,185,360,1,Semiurban 282 | LP002554,Male,No,0,Graduate,No,2166,2057,122,360,1,Semiurban 283 | LP002561,Male,Yes,0,Graduate,No,5000,0,126,360,1,Rural 284 | LP002566,Female,No,0,Graduate,No,5530,0,135,360,,Urban 285 | LP002568,Male,No,0,Not Graduate,No,9000,0,122,360,1,Rural 286 | LP002570,Female,Yes,2,Graduate,No,10000,11666,460,360,1,Urban 287 | LP002572,Male,Yes,1,Graduate,,8750,0,297,360,1,Urban 288 | LP002581,Male,Yes,0,Not Graduate,No,2157,2730,140,360,,Rural 289 | LP002584,Male,No,0,Graduate,,1972,4347,106,360,1,Rural 290 | LP002592,Male,No,0,Graduate,No,4983,0,141,360,1,Urban 291 | LP002593,Male,Yes,1,Graduate,No,8333,4000,,360,1,Urban 292 | LP002599,Male,Yes,0,Graduate,No,3667,2000,170,360,1,Semiurban 293 | LP002604,Male,Yes,2,Graduate,No,3166,2833,145,360,1,Urban 294 | LP002605,Male,No,0,Not Graduate,No,3271,0,90,360,1,Rural 295 | LP002609,Female,Yes,0,Graduate,No,2241,2000,88,360,0,Urban 296 | LP002610,Male,Yes,1,Not Graduate,,1792,2565,128,360,1,Urban 297 | LP002612,Female,Yes,0,Graduate,No,2666,0,84,480,1,Semiurban 298 | LP002614,,No,0,Graduate,No,6478,0,108,360,1,Semiurban 299 | LP002630,Male,No,0,Not Graduate,,3808,0,83,360,1,Rural 300 | LP002635,Female,Yes,2,Not Graduate,No,3729,0,117,360,1,Semiurban 301 | LP002639,Male,Yes,2,Graduate,No,4120,0,128,360,1,Rural 302 | LP002644,Male,Yes,1,Graduate,Yes,7500,0,75,360,1,Urban 303 | LP002651,Male,Yes,1,Graduate,,6300,0,125,360,0,Urban 304 | LP002654,Female,No,,Graduate,Yes,14987,0,177,360,1,Rural 305 | LP002657,,Yes,1,Not Graduate,Yes,570,2125,68,360,1,Rural 306 | LP002711,Male,Yes,0,Graduate,No,2600,700,96,360,1,Semiurban 307 | LP002712,Male,No,2,Not Graduate,No,2733,1083,180,360,,Semiurban 308 | LP002721,Male,Yes,2,Graduate,Yes,7500,0,183,360,1,Rural 309 | LP002735,Male,Yes,2,Not Graduate,No,3859,0,121,360,1,Rural 310 | LP002744,Male,Yes,1,Graduate,No,6825,0,162,360,1,Rural 311 | LP002745,Male,Yes,0,Graduate,No,3708,4700,132,360,1,Semiurban 312 | LP002746,Male,No,0,Graduate,No,5314,0,147,360,1,Urban 313 | LP002747,Female,No,3+,Graduate,No,2366,5272,153,360,0,Rural 314 | LP002754,Male,No,,Graduate,No,2066,2108,104,84,1,Urban 315 | LP002759,Male,Yes,2,Graduate,No,5000,0,149,360,1,Rural 316 | LP002760,Female,No,0,Graduate,No,3767,0,134,300,1,Urban 317 | LP002766,Female,Yes,0,Graduate,No,7859,879,165,180,1,Semiurban 318 | LP002769,Female,Yes,0,Graduate,No,4283,0,120,360,1,Rural 319 | LP002774,Male,Yes,0,Not Graduate,No,1700,2900,67,360,0,Urban 320 | LP002775,,No,0,Not Graduate,No,4768,0,125,360,1,Rural 321 | LP002781,Male,No,0,Graduate,No,3083,2738,120,360,1,Urban 322 | LP002782,Male,Yes,1,Graduate,No,2667,1542,148,360,1,Rural 323 | LP002786,Female,Yes,0,Not Graduate,No,1647,1762,181,360,1,Urban 324 | LP002790,Male,Yes,3+,Graduate,No,3400,0,80,120,1,Urban 325 | LP002791,Male,No,1,Graduate,,16000,5000,40,360,1,Semiurban 326 | LP002793,Male,Yes,0,Graduate,No,5333,0,90,360,1,Rural 327 | LP002802,Male,No,0,Graduate,No,2875,2416,95,6,0,Semiurban 328 | LP002803,Male,Yes,1,Not Graduate,,2600,618,122,360,1,Semiurban 329 | LP002805,Male,Yes,2,Graduate,No,5041,700,150,360,1,Urban 330 | LP002806,Male,Yes,3+,Graduate,Yes,6958,1411,150,360,1,Rural 331 | LP002816,Male,Yes,1,Graduate,No,3500,1658,104,360,,Semiurban 332 | LP002823,Male,Yes,0,Graduate,No,5509,0,143,360,1,Rural 333 | LP002825,Male,Yes,3+,Graduate,No,9699,0,300,360,1,Urban 334 | LP002826,Female,Yes,1,Not Graduate,No,3621,2717,171,360,1,Urban 335 | LP002843,Female,Yes,0,Graduate,No,4709,0,113,360,1,Semiurban 336 | LP002849,Male,Yes,0,Graduate,No,1516,1951,35,360,1,Semiurban 337 | LP002850,Male,No,2,Graduate,No,2400,0,46,360,1,Urban 338 | LP002853,Female,No,0,Not Graduate,No,3015,2000,145,360,,Urban 339 | LP002856,Male,Yes,0,Graduate,No,2292,1558,119,360,1,Urban 340 | LP002857,Male,Yes,1,Graduate,Yes,2360,3355,87,240,1,Rural 341 | LP002858,Female,No,0,Graduate,No,4333,2333,162,360,0,Rural 342 | LP002860,Male,Yes,0,Graduate,Yes,2623,4831,122,180,1,Semiurban 343 | LP002867,Male,No,0,Graduate,Yes,3972,4275,187,360,1,Rural 344 | LP002869,Male,Yes,3+,Not Graduate,No,3522,0,81,180,1,Rural 345 | LP002870,Male,Yes,1,Graduate,No,4700,0,80,360,1,Urban 346 | LP002876,Male,No,0,Graduate,No,6858,0,176,360,1,Rural 347 | LP002878,Male,Yes,3+,Graduate,No,8334,0,260,360,1,Urban 348 | LP002879,Male,Yes,0,Graduate,No,3391,1966,133,360,0,Rural 349 | LP002885,Male,No,0,Not Graduate,No,2868,0,70,360,1,Urban 350 | LP002890,Male,Yes,2,Not Graduate,No,3418,1380,135,360,1,Urban 351 | LP002891,Male,Yes,0,Graduate,Yes,2500,296,137,300,1,Rural 352 | LP002899,Male,Yes,2,Graduate,No,8667,0,254,360,1,Rural 353 | LP002901,Male,No,0,Graduate,No,2283,15000,106,360,,Rural 354 | LP002907,Male,Yes,0,Graduate,No,5817,910,109,360,1,Urban 355 | LP002920,Male,Yes,0,Graduate,No,5119,3769,120,360,1,Rural 356 | LP002921,Male,Yes,3+,Not Graduate,No,5316,187,158,180,0,Semiurban 357 | LP002932,Male,Yes,3+,Graduate,No,7603,1213,197,360,1,Urban 358 | LP002935,Male,Yes,1,Graduate,No,3791,1936,85,360,1,Urban 359 | LP002952,Male,No,0,Graduate,No,2500,0,60,360,1,Urban 360 | LP002954,Male,Yes,2,Not Graduate,No,3132,0,76,360,,Rural 361 | LP002962,Male,No,0,Graduate,No,4000,2667,152,360,1,Semiurban 362 | LP002965,Female,Yes,0,Graduate,No,8550,4255,96,360,,Urban 363 | LP002969,Male,Yes,1,Graduate,No,2269,2167,99,360,1,Semiurban 364 | LP002971,Male,Yes,3+,Not Graduate,Yes,4009,1777,113,360,1,Urban 365 | LP002975,Male,Yes,0,Graduate,No,4158,709,115,360,1,Urban 366 | LP002980,Male,No,0,Graduate,No,3250,1993,126,360,,Semiurban 367 | LP002986,Male,Yes,0,Graduate,No,5000,2393,158,360,1,Rural 368 | LP002989,Male,No,0,Graduate,Yes,9200,0,98,180,1,Rural -------------------------------------------------------------------------------- /Loan Prediction/Datasets/train_ctrUa4K.csv: -------------------------------------------------------------------------------- 1 | Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status 2 | LP001002,Male,No,0,Graduate,No,5849,0,,360,1,Urban,Y 3 | LP001003,Male,Yes,1,Graduate,No,4583,1508,128,360,1,Rural,N 4 | LP001005,Male,Yes,0,Graduate,Yes,3000,0,66,360,1,Urban,Y 5 | LP001006,Male,Yes,0,Not Graduate,No,2583,2358,120,360,1,Urban,Y 6 | LP001008,Male,No,0,Graduate,No,6000,0,141,360,1,Urban,Y 7 | LP001011,Male,Yes,2,Graduate,Yes,5417,4196,267,360,1,Urban,Y 8 | LP001013,Male,Yes,0,Not Graduate,No,2333,1516,95,360,1,Urban,Y 9 | LP001014,Male,Yes,3+,Graduate,No,3036,2504,158,360,0,Semiurban,N 10 | LP001018,Male,Yes,2,Graduate,No,4006,1526,168,360,1,Urban,Y 11 | LP001020,Male,Yes,1,Graduate,No,12841,10968,349,360,1,Semiurban,N 12 | LP001024,Male,Yes,2,Graduate,No,3200,700,70,360,1,Urban,Y 13 | LP001027,Male,Yes,2,Graduate,,2500,1840,109,360,1,Urban,Y 14 | LP001028,Male,Yes,2,Graduate,No,3073,8106,200,360,1,Urban,Y 15 | LP001029,Male,No,0,Graduate,No,1853,2840,114,360,1,Rural,N 16 | LP001030,Male,Yes,2,Graduate,No,1299,1086,17,120,1,Urban,Y 17 | LP001032,Male,No,0,Graduate,No,4950,0,125,360,1,Urban,Y 18 | LP001034,Male,No,1,Not Graduate,No,3596,0,100,240,,Urban,Y 19 | LP001036,Female,No,0,Graduate,No,3510,0,76,360,0,Urban,N 20 | LP001038,Male,Yes,0,Not Graduate,No,4887,0,133,360,1,Rural,N 21 | LP001041,Male,Yes,0,Graduate,,2600,3500,115,,1,Urban,Y 22 | LP001043,Male,Yes,0,Not Graduate,No,7660,0,104,360,0,Urban,N 23 | LP001046,Male,Yes,1,Graduate,No,5955,5625,315,360,1,Urban,Y 24 | LP001047,Male,Yes,0,Not Graduate,No,2600,1911,116,360,0,Semiurban,N 25 | LP001050,,Yes,2,Not Graduate,No,3365,1917,112,360,0,Rural,N 26 | LP001052,Male,Yes,1,Graduate,,3717,2925,151,360,,Semiurban,N 27 | LP001066,Male,Yes,0,Graduate,Yes,9560,0,191,360,1,Semiurban,Y 28 | LP001068,Male,Yes,0,Graduate,No,2799,2253,122,360,1,Semiurban,Y 29 | LP001073,Male,Yes,2,Not Graduate,No,4226,1040,110,360,1,Urban,Y 30 | LP001086,Male,No,0,Not Graduate,No,1442,0,35,360,1,Urban,N 31 | LP001087,Female,No,2,Graduate,,3750,2083,120,360,1,Semiurban,Y 32 | LP001091,Male,Yes,1,Graduate,,4166,3369,201,360,,Urban,N 33 | LP001095,Male,No,0,Graduate,No,3167,0,74,360,1,Urban,N 34 | LP001097,Male,No,1,Graduate,Yes,4692,0,106,360,1,Rural,N 35 | LP001098,Male,Yes,0,Graduate,No,3500,1667,114,360,1,Semiurban,Y 36 | LP001100,Male,No,3+,Graduate,No,12500,3000,320,360,1,Rural,N 37 | LP001106,Male,Yes,0,Graduate,No,2275,2067,,360,1,Urban,Y 38 | LP001109,Male,Yes,0,Graduate,No,1828,1330,100,,0,Urban,N 39 | LP001112,Female,Yes,0,Graduate,No,3667,1459,144,360,1,Semiurban,Y 40 | LP001114,Male,No,0,Graduate,No,4166,7210,184,360,1,Urban,Y 41 | LP001116,Male,No,0,Not Graduate,No,3748,1668,110,360,1,Semiurban,Y 42 | LP001119,Male,No,0,Graduate,No,3600,0,80,360,1,Urban,N 43 | LP001120,Male,No,0,Graduate,No,1800,1213,47,360,1,Urban,Y 44 | LP001123,Male,Yes,0,Graduate,No,2400,0,75,360,,Urban,Y 45 | LP001131,Male,Yes,0,Graduate,No,3941,2336,134,360,1,Semiurban,Y 46 | LP001136,Male,Yes,0,Not Graduate,Yes,4695,0,96,,1,Urban,Y 47 | LP001137,Female,No,0,Graduate,No,3410,0,88,,1,Urban,Y 48 | LP001138,Male,Yes,1,Graduate,No,5649,0,44,360,1,Urban,Y 49 | LP001144,Male,Yes,0,Graduate,No,5821,0,144,360,1,Urban,Y 50 | LP001146,Female,Yes,0,Graduate,No,2645,3440,120,360,0,Urban,N 51 | LP001151,Female,No,0,Graduate,No,4000,2275,144,360,1,Semiurban,Y 52 | LP001155,Female,Yes,0,Not Graduate,No,1928,1644,100,360,1,Semiurban,Y 53 | LP001157,Female,No,0,Graduate,No,3086,0,120,360,1,Semiurban,Y 54 | LP001164,Female,No,0,Graduate,No,4230,0,112,360,1,Semiurban,N 55 | LP001179,Male,Yes,2,Graduate,No,4616,0,134,360,1,Urban,N 56 | LP001186,Female,Yes,1,Graduate,Yes,11500,0,286,360,0,Urban,N 57 | LP001194,Male,Yes,2,Graduate,No,2708,1167,97,360,1,Semiurban,Y 58 | LP001195,Male,Yes,0,Graduate,No,2132,1591,96,360,1,Semiurban,Y 59 | LP001197,Male,Yes,0,Graduate,No,3366,2200,135,360,1,Rural,N 60 | LP001198,Male,Yes,1,Graduate,No,8080,2250,180,360,1,Urban,Y 61 | LP001199,Male,Yes,2,Not Graduate,No,3357,2859,144,360,1,Urban,Y 62 | LP001205,Male,Yes,0,Graduate,No,2500,3796,120,360,1,Urban,Y 63 | LP001206,Male,Yes,3+,Graduate,No,3029,0,99,360,1,Urban,Y 64 | LP001207,Male,Yes,0,Not Graduate,Yes,2609,3449,165,180,0,Rural,N 65 | LP001213,Male,Yes,1,Graduate,No,4945,0,,360,0,Rural,N 66 | LP001222,Female,No,0,Graduate,No,4166,0,116,360,0,Semiurban,N 67 | LP001225,Male,Yes,0,Graduate,No,5726,4595,258,360,1,Semiurban,N 68 | LP001228,Male,No,0,Not Graduate,No,3200,2254,126,180,0,Urban,N 69 | LP001233,Male,Yes,1,Graduate,No,10750,0,312,360,1,Urban,Y 70 | LP001238,Male,Yes,3+,Not Graduate,Yes,7100,0,125,60,1,Urban,Y 71 | LP001241,Female,No,0,Graduate,No,4300,0,136,360,0,Semiurban,N 72 | LP001243,Male,Yes,0,Graduate,No,3208,3066,172,360,1,Urban,Y 73 | LP001245,Male,Yes,2,Not Graduate,Yes,1875,1875,97,360,1,Semiurban,Y 74 | LP001248,Male,No,0,Graduate,No,3500,0,81,300,1,Semiurban,Y 75 | LP001250,Male,Yes,3+,Not Graduate,No,4755,0,95,,0,Semiurban,N 76 | LP001253,Male,Yes,3+,Graduate,Yes,5266,1774,187,360,1,Semiurban,Y 77 | LP001255,Male,No,0,Graduate,No,3750,0,113,480,1,Urban,N 78 | LP001256,Male,No,0,Graduate,No,3750,4750,176,360,1,Urban,N 79 | LP001259,Male,Yes,1,Graduate,Yes,1000,3022,110,360,1,Urban,N 80 | LP001263,Male,Yes,3+,Graduate,No,3167,4000,180,300,0,Semiurban,N 81 | LP001264,Male,Yes,3+,Not Graduate,Yes,3333,2166,130,360,,Semiurban,Y 82 | LP001265,Female,No,0,Graduate,No,3846,0,111,360,1,Semiurban,Y 83 | LP001266,Male,Yes,1,Graduate,Yes,2395,0,,360,1,Semiurban,Y 84 | LP001267,Female,Yes,2,Graduate,No,1378,1881,167,360,1,Urban,N 85 | LP001273,Male,Yes,0,Graduate,No,6000,2250,265,360,,Semiurban,N 86 | LP001275,Male,Yes,1,Graduate,No,3988,0,50,240,1,Urban,Y 87 | LP001279,Male,No,0,Graduate,No,2366,2531,136,360,1,Semiurban,Y 88 | LP001280,Male,Yes,2,Not Graduate,No,3333,2000,99,360,,Semiurban,Y 89 | LP001282,Male,Yes,0,Graduate,No,2500,2118,104,360,1,Semiurban,Y 90 | LP001289,Male,No,0,Graduate,No,8566,0,210,360,1,Urban,Y 91 | LP001310,Male,Yes,0,Graduate,No,5695,4167,175,360,1,Semiurban,Y 92 | LP001316,Male,Yes,0,Graduate,No,2958,2900,131,360,1,Semiurban,Y 93 | LP001318,Male,Yes,2,Graduate,No,6250,5654,188,180,1,Semiurban,Y 94 | LP001319,Male,Yes,2,Not Graduate,No,3273,1820,81,360,1,Urban,Y 95 | LP001322,Male,No,0,Graduate,No,4133,0,122,360,1,Semiurban,Y 96 | LP001325,Male,No,0,Not Graduate,No,3620,0,25,120,1,Semiurban,Y 97 | LP001326,Male,No,0,Graduate,,6782,0,,360,,Urban,N 98 | LP001327,Female,Yes,0,Graduate,No,2484,2302,137,360,1,Semiurban,Y 99 | LP001333,Male,Yes,0,Graduate,No,1977,997,50,360,1,Semiurban,Y 100 | LP001334,Male,Yes,0,Not Graduate,No,4188,0,115,180,1,Semiurban,Y 101 | LP001343,Male,Yes,0,Graduate,No,1759,3541,131,360,1,Semiurban,Y 102 | LP001345,Male,Yes,2,Not Graduate,No,4288,3263,133,180,1,Urban,Y 103 | LP001349,Male,No,0,Graduate,No,4843,3806,151,360,1,Semiurban,Y 104 | LP001350,Male,Yes,,Graduate,No,13650,0,,360,1,Urban,Y 105 | LP001356,Male,Yes,0,Graduate,No,4652,3583,,360,1,Semiurban,Y 106 | LP001357,Male,,,Graduate,No,3816,754,160,360,1,Urban,Y 107 | LP001367,Male,Yes,1,Graduate,No,3052,1030,100,360,1,Urban,Y 108 | LP001369,Male,Yes,2,Graduate,No,11417,1126,225,360,1,Urban,Y 109 | LP001370,Male,No,0,Not Graduate,,7333,0,120,360,1,Rural,N 110 | LP001379,Male,Yes,2,Graduate,No,3800,3600,216,360,0,Urban,N 111 | LP001384,Male,Yes,3+,Not Graduate,No,2071,754,94,480,1,Semiurban,Y 112 | LP001385,Male,No,0,Graduate,No,5316,0,136,360,1,Urban,Y 113 | LP001387,Female,Yes,0,Graduate,,2929,2333,139,360,1,Semiurban,Y 114 | LP001391,Male,Yes,0,Not Graduate,No,3572,4114,152,,0,Rural,N 115 | LP001392,Female,No,1,Graduate,Yes,7451,0,,360,1,Semiurban,Y 116 | LP001398,Male,No,0,Graduate,,5050,0,118,360,1,Semiurban,Y 117 | LP001401,Male,Yes,1,Graduate,No,14583,0,185,180,1,Rural,Y 118 | LP001404,Female,Yes,0,Graduate,No,3167,2283,154,360,1,Semiurban,Y 119 | LP001405,Male,Yes,1,Graduate,No,2214,1398,85,360,,Urban,Y 120 | LP001421,Male,Yes,0,Graduate,No,5568,2142,175,360,1,Rural,N 121 | LP001422,Female,No,0,Graduate,No,10408,0,259,360,1,Urban,Y 122 | LP001426,Male,Yes,,Graduate,No,5667,2667,180,360,1,Rural,Y 123 | LP001430,Female,No,0,Graduate,No,4166,0,44,360,1,Semiurban,Y 124 | LP001431,Female,No,0,Graduate,No,2137,8980,137,360,0,Semiurban,Y 125 | LP001432,Male,Yes,2,Graduate,No,2957,0,81,360,1,Semiurban,Y 126 | LP001439,Male,Yes,0,Not Graduate,No,4300,2014,194,360,1,Rural,Y 127 | LP001443,Female,No,0,Graduate,No,3692,0,93,360,,Rural,Y 128 | LP001448,,Yes,3+,Graduate,No,23803,0,370,360,1,Rural,Y 129 | LP001449,Male,No,0,Graduate,No,3865,1640,,360,1,Rural,Y 130 | LP001451,Male,Yes,1,Graduate,Yes,10513,3850,160,180,0,Urban,N 131 | LP001465,Male,Yes,0,Graduate,No,6080,2569,182,360,,Rural,N 132 | LP001469,Male,No,0,Graduate,Yes,20166,0,650,480,,Urban,Y 133 | LP001473,Male,No,0,Graduate,No,2014,1929,74,360,1,Urban,Y 134 | LP001478,Male,No,0,Graduate,No,2718,0,70,360,1,Semiurban,Y 135 | LP001482,Male,Yes,0,Graduate,Yes,3459,0,25,120,1,Semiurban,Y 136 | LP001487,Male,No,0,Graduate,No,4895,0,102,360,1,Semiurban,Y 137 | LP001488,Male,Yes,3+,Graduate,No,4000,7750,290,360,1,Semiurban,N 138 | LP001489,Female,Yes,0,Graduate,No,4583,0,84,360,1,Rural,N 139 | LP001491,Male,Yes,2,Graduate,Yes,3316,3500,88,360,1,Urban,Y 140 | LP001492,Male,No,0,Graduate,No,14999,0,242,360,0,Semiurban,N 141 | LP001493,Male,Yes,2,Not Graduate,No,4200,1430,129,360,1,Rural,N 142 | LP001497,Male,Yes,2,Graduate,No,5042,2083,185,360,1,Rural,N 143 | LP001498,Male,No,0,Graduate,No,5417,0,168,360,1,Urban,Y 144 | LP001504,Male,No,0,Graduate,Yes,6950,0,175,180,1,Semiurban,Y 145 | LP001507,Male,Yes,0,Graduate,No,2698,2034,122,360,1,Semiurban,Y 146 | LP001508,Male,Yes,2,Graduate,No,11757,0,187,180,1,Urban,Y 147 | LP001514,Female,Yes,0,Graduate,No,2330,4486,100,360,1,Semiurban,Y 148 | LP001516,Female,Yes,2,Graduate,No,14866,0,70,360,1,Urban,Y 149 | LP001518,Male,Yes,1,Graduate,No,1538,1425,30,360,1,Urban,Y 150 | LP001519,Female,No,0,Graduate,No,10000,1666,225,360,1,Rural,N 151 | LP001520,Male,Yes,0,Graduate,No,4860,830,125,360,1,Semiurban,Y 152 | LP001528,Male,No,0,Graduate,No,6277,0,118,360,0,Rural,N 153 | LP001529,Male,Yes,0,Graduate,Yes,2577,3750,152,360,1,Rural,Y 154 | LP001531,Male,No,0,Graduate,No,9166,0,244,360,1,Urban,N 155 | LP001532,Male,Yes,2,Not Graduate,No,2281,0,113,360,1,Rural,N 156 | LP001535,Male,No,0,Graduate,No,3254,0,50,360,1,Urban,Y 157 | LP001536,Male,Yes,3+,Graduate,No,39999,0,600,180,0,Semiurban,Y 158 | LP001541,Male,Yes,1,Graduate,No,6000,0,160,360,,Rural,Y 159 | LP001543,Male,Yes,1,Graduate,No,9538,0,187,360,1,Urban,Y 160 | LP001546,Male,No,0,Graduate,,2980,2083,120,360,1,Rural,Y 161 | LP001552,Male,Yes,0,Graduate,No,4583,5625,255,360,1,Semiurban,Y 162 | LP001560,Male,Yes,0,Not Graduate,No,1863,1041,98,360,1,Semiurban,Y 163 | LP001562,Male,Yes,0,Graduate,No,7933,0,275,360,1,Urban,N 164 | LP001565,Male,Yes,1,Graduate,No,3089,1280,121,360,0,Semiurban,N 165 | LP001570,Male,Yes,2,Graduate,No,4167,1447,158,360,1,Rural,Y 166 | LP001572,Male,Yes,0,Graduate,No,9323,0,75,180,1,Urban,Y 167 | LP001574,Male,Yes,0,Graduate,No,3707,3166,182,,1,Rural,Y 168 | LP001577,Female,Yes,0,Graduate,No,4583,0,112,360,1,Rural,N 169 | LP001578,Male,Yes,0,Graduate,No,2439,3333,129,360,1,Rural,Y 170 | LP001579,Male,No,0,Graduate,No,2237,0,63,480,0,Semiurban,N 171 | LP001580,Male,Yes,2,Graduate,No,8000,0,200,360,1,Semiurban,Y 172 | LP001581,Male,Yes,0,Not Graduate,,1820,1769,95,360,1,Rural,Y 173 | LP001585,,Yes,3+,Graduate,No,51763,0,700,300,1,Urban,Y 174 | LP001586,Male,Yes,3+,Not Graduate,No,3522,0,81,180,1,Rural,N 175 | LP001594,Male,Yes,0,Graduate,No,5708,5625,187,360,1,Semiurban,Y 176 | LP001603,Male,Yes,0,Not Graduate,Yes,4344,736,87,360,1,Semiurban,N 177 | LP001606,Male,Yes,0,Graduate,No,3497,1964,116,360,1,Rural,Y 178 | LP001608,Male,Yes,2,Graduate,No,2045,1619,101,360,1,Rural,Y 179 | LP001610,Male,Yes,3+,Graduate,No,5516,11300,495,360,0,Semiurban,N 180 | LP001616,Male,Yes,1,Graduate,No,3750,0,116,360,1,Semiurban,Y 181 | LP001630,Male,No,0,Not Graduate,No,2333,1451,102,480,0,Urban,N 182 | LP001633,Male,Yes,1,Graduate,No,6400,7250,180,360,0,Urban,N 183 | LP001634,Male,No,0,Graduate,No,1916,5063,67,360,,Rural,N 184 | LP001636,Male,Yes,0,Graduate,No,4600,0,73,180,1,Semiurban,Y 185 | LP001637,Male,Yes,1,Graduate,No,33846,0,260,360,1,Semiurban,N 186 | LP001639,Female,Yes,0,Graduate,No,3625,0,108,360,1,Semiurban,Y 187 | LP001640,Male,Yes,0,Graduate,Yes,39147,4750,120,360,1,Semiurban,Y 188 | LP001641,Male,Yes,1,Graduate,Yes,2178,0,66,300,0,Rural,N 189 | LP001643,Male,Yes,0,Graduate,No,2383,2138,58,360,,Rural,Y 190 | LP001644,,Yes,0,Graduate,Yes,674,5296,168,360,1,Rural,Y 191 | LP001647,Male,Yes,0,Graduate,No,9328,0,188,180,1,Rural,Y 192 | LP001653,Male,No,0,Not Graduate,No,4885,0,48,360,1,Rural,Y 193 | LP001656,Male,No,0,Graduate,No,12000,0,164,360,1,Semiurban,N 194 | LP001657,Male,Yes,0,Not Graduate,No,6033,0,160,360,1,Urban,N 195 | LP001658,Male,No,0,Graduate,No,3858,0,76,360,1,Semiurban,Y 196 | LP001664,Male,No,0,Graduate,No,4191,0,120,360,1,Rural,Y 197 | LP001665,Male,Yes,1,Graduate,No,3125,2583,170,360,1,Semiurban,N 198 | LP001666,Male,No,0,Graduate,No,8333,3750,187,360,1,Rural,Y 199 | LP001669,Female,No,0,Not Graduate,No,1907,2365,120,,1,Urban,Y 200 | LP001671,Female,Yes,0,Graduate,No,3416,2816,113,360,,Semiurban,Y 201 | LP001673,Male,No,0,Graduate,Yes,11000,0,83,360,1,Urban,N 202 | LP001674,Male,Yes,1,Not Graduate,No,2600,2500,90,360,1,Semiurban,Y 203 | LP001677,Male,No,2,Graduate,No,4923,0,166,360,0,Semiurban,Y 204 | LP001682,Male,Yes,3+,Not Graduate,No,3992,0,,180,1,Urban,N 205 | LP001688,Male,Yes,1,Not Graduate,No,3500,1083,135,360,1,Urban,Y 206 | LP001691,Male,Yes,2,Not Graduate,No,3917,0,124,360,1,Semiurban,Y 207 | LP001692,Female,No,0,Not Graduate,No,4408,0,120,360,1,Semiurban,Y 208 | LP001693,Female,No,0,Graduate,No,3244,0,80,360,1,Urban,Y 209 | LP001698,Male,No,0,Not Graduate,No,3975,2531,55,360,1,Rural,Y 210 | LP001699,Male,No,0,Graduate,No,2479,0,59,360,1,Urban,Y 211 | LP001702,Male,No,0,Graduate,No,3418,0,127,360,1,Semiurban,N 212 | LP001708,Female,No,0,Graduate,No,10000,0,214,360,1,Semiurban,N 213 | LP001711,Male,Yes,3+,Graduate,No,3430,1250,128,360,0,Semiurban,N 214 | LP001713,Male,Yes,1,Graduate,Yes,7787,0,240,360,1,Urban,Y 215 | LP001715,Male,Yes,3+,Not Graduate,Yes,5703,0,130,360,1,Rural,Y 216 | LP001716,Male,Yes,0,Graduate,No,3173,3021,137,360,1,Urban,Y 217 | LP001720,Male,Yes,3+,Not Graduate,No,3850,983,100,360,1,Semiurban,Y 218 | LP001722,Male,Yes,0,Graduate,No,150,1800,135,360,1,Rural,N 219 | LP001726,Male,Yes,0,Graduate,No,3727,1775,131,360,1,Semiurban,Y 220 | LP001732,Male,Yes,2,Graduate,,5000,0,72,360,0,Semiurban,N 221 | LP001734,Female,Yes,2,Graduate,No,4283,2383,127,360,,Semiurban,Y 222 | LP001736,Male,Yes,0,Graduate,No,2221,0,60,360,0,Urban,N 223 | LP001743,Male,Yes,2,Graduate,No,4009,1717,116,360,1,Semiurban,Y 224 | LP001744,Male,No,0,Graduate,No,2971,2791,144,360,1,Semiurban,Y 225 | LP001749,Male,Yes,0,Graduate,No,7578,1010,175,,1,Semiurban,Y 226 | LP001750,Male,Yes,0,Graduate,No,6250,0,128,360,1,Semiurban,Y 227 | LP001751,Male,Yes,0,Graduate,No,3250,0,170,360,1,Rural,N 228 | LP001754,Male,Yes,,Not Graduate,Yes,4735,0,138,360,1,Urban,N 229 | LP001758,Male,Yes,2,Graduate,No,6250,1695,210,360,1,Semiurban,Y 230 | LP001760,Male,,,Graduate,No,4758,0,158,480,1,Semiurban,Y 231 | LP001761,Male,No,0,Graduate,Yes,6400,0,200,360,1,Rural,Y 232 | LP001765,Male,Yes,1,Graduate,No,2491,2054,104,360,1,Semiurban,Y 233 | LP001768,Male,Yes,0,Graduate,,3716,0,42,180,1,Rural,Y 234 | LP001770,Male,No,0,Not Graduate,No,3189,2598,120,,1,Rural,Y 235 | LP001776,Female,No,0,Graduate,No,8333,0,280,360,1,Semiurban,Y 236 | LP001778,Male,Yes,1,Graduate,No,3155,1779,140,360,1,Semiurban,Y 237 | LP001784,Male,Yes,1,Graduate,No,5500,1260,170,360,1,Rural,Y 238 | LP001786,Male,Yes,0,Graduate,,5746,0,255,360,,Urban,N 239 | LP001788,Female,No,0,Graduate,Yes,3463,0,122,360,,Urban,Y 240 | LP001790,Female,No,1,Graduate,No,3812,0,112,360,1,Rural,Y 241 | LP001792,Male,Yes,1,Graduate,No,3315,0,96,360,1,Semiurban,Y 242 | LP001798,Male,Yes,2,Graduate,No,5819,5000,120,360,1,Rural,Y 243 | LP001800,Male,Yes,1,Not Graduate,No,2510,1983,140,180,1,Urban,N 244 | LP001806,Male,No,0,Graduate,No,2965,5701,155,60,1,Urban,Y 245 | LP001807,Male,Yes,2,Graduate,Yes,6250,1300,108,360,1,Rural,Y 246 | LP001811,Male,Yes,0,Not Graduate,No,3406,4417,123,360,1,Semiurban,Y 247 | LP001813,Male,No,0,Graduate,Yes,6050,4333,120,180,1,Urban,N 248 | LP001814,Male,Yes,2,Graduate,No,9703,0,112,360,1,Urban,Y 249 | LP001819,Male,Yes,1,Not Graduate,No,6608,0,137,180,1,Urban,Y 250 | LP001824,Male,Yes,1,Graduate,No,2882,1843,123,480,1,Semiurban,Y 251 | LP001825,Male,Yes,0,Graduate,No,1809,1868,90,360,1,Urban,Y 252 | LP001835,Male,Yes,0,Not Graduate,No,1668,3890,201,360,0,Semiurban,N 253 | LP001836,Female,No,2,Graduate,No,3427,0,138,360,1,Urban,N 254 | LP001841,Male,No,0,Not Graduate,Yes,2583,2167,104,360,1,Rural,Y 255 | LP001843,Male,Yes,1,Not Graduate,No,2661,7101,279,180,1,Semiurban,Y 256 | LP001844,Male,No,0,Graduate,Yes,16250,0,192,360,0,Urban,N 257 | LP001846,Female,No,3+,Graduate,No,3083,0,255,360,1,Rural,Y 258 | LP001849,Male,No,0,Not Graduate,No,6045,0,115,360,0,Rural,N 259 | LP001854,Male,Yes,3+,Graduate,No,5250,0,94,360,1,Urban,N 260 | LP001859,Male,Yes,0,Graduate,No,14683,2100,304,360,1,Rural,N 261 | LP001864,Male,Yes,3+,Not Graduate,No,4931,0,128,360,,Semiurban,N 262 | LP001865,Male,Yes,1,Graduate,No,6083,4250,330,360,,Urban,Y 263 | LP001868,Male,No,0,Graduate,No,2060,2209,134,360,1,Semiurban,Y 264 | LP001870,Female,No,1,Graduate,No,3481,0,155,36,1,Semiurban,N 265 | LP001871,Female,No,0,Graduate,No,7200,0,120,360,1,Rural,Y 266 | LP001872,Male,No,0,Graduate,Yes,5166,0,128,360,1,Semiurban,Y 267 | LP001875,Male,No,0,Graduate,No,4095,3447,151,360,1,Rural,Y 268 | LP001877,Male,Yes,2,Graduate,No,4708,1387,150,360,1,Semiurban,Y 269 | LP001882,Male,Yes,3+,Graduate,No,4333,1811,160,360,0,Urban,Y 270 | LP001883,Female,No,0,Graduate,,3418,0,135,360,1,Rural,N 271 | LP001884,Female,No,1,Graduate,No,2876,1560,90,360,1,Urban,Y 272 | LP001888,Female,No,0,Graduate,No,3237,0,30,360,1,Urban,Y 273 | LP001891,Male,Yes,0,Graduate,No,11146,0,136,360,1,Urban,Y 274 | LP001892,Male,No,0,Graduate,No,2833,1857,126,360,1,Rural,Y 275 | LP001894,Male,Yes,0,Graduate,No,2620,2223,150,360,1,Semiurban,Y 276 | LP001896,Male,Yes,2,Graduate,No,3900,0,90,360,1,Semiurban,Y 277 | LP001900,Male,Yes,1,Graduate,No,2750,1842,115,360,1,Semiurban,Y 278 | LP001903,Male,Yes,0,Graduate,No,3993,3274,207,360,1,Semiurban,Y 279 | LP001904,Male,Yes,0,Graduate,No,3103,1300,80,360,1,Urban,Y 280 | LP001907,Male,Yes,0,Graduate,No,14583,0,436,360,1,Semiurban,Y 281 | LP001908,Female,Yes,0,Not Graduate,No,4100,0,124,360,,Rural,Y 282 | LP001910,Male,No,1,Not Graduate,Yes,4053,2426,158,360,0,Urban,N 283 | LP001914,Male,Yes,0,Graduate,No,3927,800,112,360,1,Semiurban,Y 284 | LP001915,Male,Yes,2,Graduate,No,2301,985.7999878,78,180,1,Urban,Y 285 | LP001917,Female,No,0,Graduate,No,1811,1666,54,360,1,Urban,Y 286 | LP001922,Male,Yes,0,Graduate,No,20667,0,,360,1,Rural,N 287 | LP001924,Male,No,0,Graduate,No,3158,3053,89,360,1,Rural,Y 288 | LP001925,Female,No,0,Graduate,Yes,2600,1717,99,300,1,Semiurban,N 289 | LP001926,Male,Yes,0,Graduate,No,3704,2000,120,360,1,Rural,Y 290 | LP001931,Female,No,0,Graduate,No,4124,0,115,360,1,Semiurban,Y 291 | LP001935,Male,No,0,Graduate,No,9508,0,187,360,1,Rural,Y 292 | LP001936,Male,Yes,0,Graduate,No,3075,2416,139,360,1,Rural,Y 293 | LP001938,Male,Yes,2,Graduate,No,4400,0,127,360,0,Semiurban,N 294 | LP001940,Male,Yes,2,Graduate,No,3153,1560,134,360,1,Urban,Y 295 | LP001945,Female,No,,Graduate,No,5417,0,143,480,0,Urban,N 296 | LP001947,Male,Yes,0,Graduate,No,2383,3334,172,360,1,Semiurban,Y 297 | LP001949,Male,Yes,3+,Graduate,,4416,1250,110,360,1,Urban,Y 298 | LP001953,Male,Yes,1,Graduate,No,6875,0,200,360,1,Semiurban,Y 299 | LP001954,Female,Yes,1,Graduate,No,4666,0,135,360,1,Urban,Y 300 | LP001955,Female,No,0,Graduate,No,5000,2541,151,480,1,Rural,N 301 | LP001963,Male,Yes,1,Graduate,No,2014,2925,113,360,1,Urban,N 302 | LP001964,Male,Yes,0,Not Graduate,No,1800,2934,93,360,0,Urban,N 303 | LP001972,Male,Yes,,Not Graduate,No,2875,1750,105,360,1,Semiurban,Y 304 | LP001974,Female,No,0,Graduate,No,5000,0,132,360,1,Rural,Y 305 | LP001977,Male,Yes,1,Graduate,No,1625,1803,96,360,1,Urban,Y 306 | LP001978,Male,No,0,Graduate,No,4000,2500,140,360,1,Rural,Y 307 | LP001990,Male,No,0,Not Graduate,No,2000,0,,360,1,Urban,N 308 | LP001993,Female,No,0,Graduate,No,3762,1666,135,360,1,Rural,Y 309 | LP001994,Female,No,0,Graduate,No,2400,1863,104,360,0,Urban,N 310 | LP001996,Male,No,0,Graduate,No,20233,0,480,360,1,Rural,N 311 | LP001998,Male,Yes,2,Not Graduate,No,7667,0,185,360,,Rural,Y 312 | LP002002,Female,No,0,Graduate,No,2917,0,84,360,1,Semiurban,Y 313 | LP002004,Male,No,0,Not Graduate,No,2927,2405,111,360,1,Semiurban,Y 314 | LP002006,Female,No,0,Graduate,No,2507,0,56,360,1,Rural,Y 315 | LP002008,Male,Yes,2,Graduate,Yes,5746,0,144,84,,Rural,Y 316 | LP002024,,Yes,0,Graduate,No,2473,1843,159,360,1,Rural,N 317 | LP002031,Male,Yes,1,Not Graduate,No,3399,1640,111,180,1,Urban,Y 318 | LP002035,Male,Yes,2,Graduate,No,3717,0,120,360,1,Semiurban,Y 319 | LP002036,Male,Yes,0,Graduate,No,2058,2134,88,360,,Urban,Y 320 | LP002043,Female,No,1,Graduate,No,3541,0,112,360,,Semiurban,Y 321 | LP002050,Male,Yes,1,Graduate,Yes,10000,0,155,360,1,Rural,N 322 | LP002051,Male,Yes,0,Graduate,No,2400,2167,115,360,1,Semiurban,Y 323 | LP002053,Male,Yes,3+,Graduate,No,4342,189,124,360,1,Semiurban,Y 324 | LP002054,Male,Yes,2,Not Graduate,No,3601,1590,,360,1,Rural,Y 325 | LP002055,Female,No,0,Graduate,No,3166,2985,132,360,,Rural,Y 326 | LP002065,Male,Yes,3+,Graduate,No,15000,0,300,360,1,Rural,Y 327 | LP002067,Male,Yes,1,Graduate,Yes,8666,4983,376,360,0,Rural,N 328 | LP002068,Male,No,0,Graduate,No,4917,0,130,360,0,Rural,Y 329 | LP002082,Male,Yes,0,Graduate,Yes,5818,2160,184,360,1,Semiurban,Y 330 | LP002086,Female,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N 331 | LP002087,Female,No,0,Graduate,No,2500,0,67,360,1,Urban,Y 332 | LP002097,Male,No,1,Graduate,No,4384,1793,117,360,1,Urban,Y 333 | LP002098,Male,No,0,Graduate,No,2935,0,98,360,1,Semiurban,Y 334 | LP002100,Male,No,,Graduate,No,2833,0,71,360,1,Urban,Y 335 | LP002101,Male,Yes,0,Graduate,,63337,0,490,180,1,Urban,Y 336 | LP002103,,Yes,1,Graduate,Yes,9833,1833,182,180,1,Urban,Y 337 | LP002106,Male,Yes,,Graduate,Yes,5503,4490,70,,1,Semiurban,Y 338 | LP002110,Male,Yes,1,Graduate,,5250,688,160,360,1,Rural,Y 339 | LP002112,Male,Yes,2,Graduate,Yes,2500,4600,176,360,1,Rural,Y 340 | LP002113,Female,No,3+,Not Graduate,No,1830,0,,360,0,Urban,N 341 | LP002114,Female,No,0,Graduate,No,4160,0,71,360,1,Semiurban,Y 342 | LP002115,Male,Yes,3+,Not Graduate,No,2647,1587,173,360,1,Rural,N 343 | LP002116,Female,No,0,Graduate,No,2378,0,46,360,1,Rural,N 344 | LP002119,Male,Yes,1,Not Graduate,No,4554,1229,158,360,1,Urban,Y 345 | LP002126,Male,Yes,3+,Not Graduate,No,3173,0,74,360,1,Semiurban,Y 346 | LP002128,Male,Yes,2,Graduate,,2583,2330,125,360,1,Rural,Y 347 | LP002129,Male,Yes,0,Graduate,No,2499,2458,160,360,1,Semiurban,Y 348 | LP002130,Male,Yes,,Not Graduate,No,3523,3230,152,360,0,Rural,N 349 | LP002131,Male,Yes,2,Not Graduate,No,3083,2168,126,360,1,Urban,Y 350 | LP002137,Male,Yes,0,Graduate,No,6333,4583,259,360,,Semiurban,Y 351 | LP002138,Male,Yes,0,Graduate,No,2625,6250,187,360,1,Rural,Y 352 | LP002139,Male,Yes,0,Graduate,No,9083,0,228,360,1,Semiurban,Y 353 | LP002140,Male,No,0,Graduate,No,8750,4167,308,360,1,Rural,N 354 | LP002141,Male,Yes,3+,Graduate,No,2666,2083,95,360,1,Rural,Y 355 | LP002142,Female,Yes,0,Graduate,Yes,5500,0,105,360,0,Rural,N 356 | LP002143,Female,Yes,0,Graduate,No,2423,505,130,360,1,Semiurban,Y 357 | LP002144,Female,No,,Graduate,No,3813,0,116,180,1,Urban,Y 358 | LP002149,Male,Yes,2,Graduate,No,8333,3167,165,360,1,Rural,Y 359 | LP002151,Male,Yes,1,Graduate,No,3875,0,67,360,1,Urban,N 360 | LP002158,Male,Yes,0,Not Graduate,No,3000,1666,100,480,0,Urban,N 361 | LP002160,Male,Yes,3+,Graduate,No,5167,3167,200,360,1,Semiurban,Y 362 | LP002161,Female,No,1,Graduate,No,4723,0,81,360,1,Semiurban,N 363 | LP002170,Male,Yes,2,Graduate,No,5000,3667,236,360,1,Semiurban,Y 364 | LP002175,Male,Yes,0,Graduate,No,4750,2333,130,360,1,Urban,Y 365 | LP002178,Male,Yes,0,Graduate,No,3013,3033,95,300,,Urban,Y 366 | LP002180,Male,No,0,Graduate,Yes,6822,0,141,360,1,Rural,Y 367 | LP002181,Male,No,0,Not Graduate,No,6216,0,133,360,1,Rural,N 368 | LP002187,Male,No,0,Graduate,No,2500,0,96,480,1,Semiurban,N 369 | LP002188,Male,No,0,Graduate,No,5124,0,124,,0,Rural,N 370 | LP002190,Male,Yes,1,Graduate,No,6325,0,175,360,1,Semiurban,Y 371 | LP002191,Male,Yes,0,Graduate,No,19730,5266,570,360,1,Rural,N 372 | LP002194,Female,No,0,Graduate,Yes,15759,0,55,360,1,Semiurban,Y 373 | LP002197,Male,Yes,2,Graduate,No,5185,0,155,360,1,Semiurban,Y 374 | LP002201,Male,Yes,2,Graduate,Yes,9323,7873,380,300,1,Rural,Y 375 | LP002205,Male,No,1,Graduate,No,3062,1987,111,180,0,Urban,N 376 | LP002209,Female,No,0,Graduate,,2764,1459,110,360,1,Urban,Y 377 | LP002211,Male,Yes,0,Graduate,No,4817,923,120,180,1,Urban,Y 378 | LP002219,Male,Yes,3+,Graduate,No,8750,4996,130,360,1,Rural,Y 379 | LP002223,Male,Yes,0,Graduate,No,4310,0,130,360,,Semiurban,Y 380 | LP002224,Male,No,0,Graduate,No,3069,0,71,480,1,Urban,N 381 | LP002225,Male,Yes,2,Graduate,No,5391,0,130,360,1,Urban,Y 382 | LP002226,Male,Yes,0,Graduate,,3333,2500,128,360,1,Semiurban,Y 383 | LP002229,Male,No,0,Graduate,No,5941,4232,296,360,1,Semiurban,Y 384 | LP002231,Female,No,0,Graduate,No,6000,0,156,360,1,Urban,Y 385 | LP002234,Male,No,0,Graduate,Yes,7167,0,128,360,1,Urban,Y 386 | LP002236,Male,Yes,2,Graduate,No,4566,0,100,360,1,Urban,N 387 | LP002237,Male,No,1,Graduate,,3667,0,113,180,1,Urban,Y 388 | LP002239,Male,No,0,Not Graduate,No,2346,1600,132,360,1,Semiurban,Y 389 | LP002243,Male,Yes,0,Not Graduate,No,3010,3136,,360,0,Urban,N 390 | LP002244,Male,Yes,0,Graduate,No,2333,2417,136,360,1,Urban,Y 391 | LP002250,Male,Yes,0,Graduate,No,5488,0,125,360,1,Rural,Y 392 | LP002255,Male,No,3+,Graduate,No,9167,0,185,360,1,Rural,Y 393 | LP002262,Male,Yes,3+,Graduate,No,9504,0,275,360,1,Rural,Y 394 | LP002263,Male,Yes,0,Graduate,No,2583,2115,120,360,,Urban,Y 395 | LP002265,Male,Yes,2,Not Graduate,No,1993,1625,113,180,1,Semiurban,Y 396 | LP002266,Male,Yes,2,Graduate,No,3100,1400,113,360,1,Urban,Y 397 | LP002272,Male,Yes,2,Graduate,No,3276,484,135,360,,Semiurban,Y 398 | LP002277,Female,No,0,Graduate,No,3180,0,71,360,0,Urban,N 399 | LP002281,Male,Yes,0,Graduate,No,3033,1459,95,360,1,Urban,Y 400 | LP002284,Male,No,0,Not Graduate,No,3902,1666,109,360,1,Rural,Y 401 | LP002287,Female,No,0,Graduate,No,1500,1800,103,360,0,Semiurban,N 402 | LP002288,Male,Yes,2,Not Graduate,No,2889,0,45,180,0,Urban,N 403 | LP002296,Male,No,0,Not Graduate,No,2755,0,65,300,1,Rural,N 404 | LP002297,Male,No,0,Graduate,No,2500,20000,103,360,1,Semiurban,Y 405 | LP002300,Female,No,0,Not Graduate,No,1963,0,53,360,1,Semiurban,Y 406 | LP002301,Female,No,0,Graduate,Yes,7441,0,194,360,1,Rural,N 407 | LP002305,Female,No,0,Graduate,No,4547,0,115,360,1,Semiurban,Y 408 | LP002308,Male,Yes,0,Not Graduate,No,2167,2400,115,360,1,Urban,Y 409 | LP002314,Female,No,0,Not Graduate,No,2213,0,66,360,1,Rural,Y 410 | LP002315,Male,Yes,1,Graduate,No,8300,0,152,300,0,Semiurban,N 411 | LP002317,Male,Yes,3+,Graduate,No,81000,0,360,360,0,Rural,N 412 | LP002318,Female,No,1,Not Graduate,Yes,3867,0,62,360,1,Semiurban,N 413 | LP002319,Male,Yes,0,Graduate,,6256,0,160,360,,Urban,Y 414 | LP002328,Male,Yes,0,Not Graduate,No,6096,0,218,360,0,Rural,N 415 | LP002332,Male,Yes,0,Not Graduate,No,2253,2033,110,360,1,Rural,Y 416 | LP002335,Female,Yes,0,Not Graduate,No,2149,3237,178,360,0,Semiurban,N 417 | LP002337,Female,No,0,Graduate,No,2995,0,60,360,1,Urban,Y 418 | LP002341,Female,No,1,Graduate,No,2600,0,160,360,1,Urban,N 419 | LP002342,Male,Yes,2,Graduate,Yes,1600,20000,239,360,1,Urban,N 420 | LP002345,Male,Yes,0,Graduate,No,1025,2773,112,360,1,Rural,Y 421 | LP002347,Male,Yes,0,Graduate,No,3246,1417,138,360,1,Semiurban,Y 422 | LP002348,Male,Yes,0,Graduate,No,5829,0,138,360,1,Rural,Y 423 | LP002357,Female,No,0,Not Graduate,No,2720,0,80,,0,Urban,N 424 | LP002361,Male,Yes,0,Graduate,No,1820,1719,100,360,1,Urban,Y 425 | LP002362,Male,Yes,1,Graduate,No,7250,1667,110,,0,Urban,N 426 | LP002364,Male,Yes,0,Graduate,No,14880,0,96,360,1,Semiurban,Y 427 | LP002366,Male,Yes,0,Graduate,No,2666,4300,121,360,1,Rural,Y 428 | LP002367,Female,No,1,Not Graduate,No,4606,0,81,360,1,Rural,N 429 | LP002368,Male,Yes,2,Graduate,No,5935,0,133,360,1,Semiurban,Y 430 | LP002369,Male,Yes,0,Graduate,No,2920,16.12000084,87,360,1,Rural,Y 431 | LP002370,Male,No,0,Not Graduate,No,2717,0,60,180,1,Urban,Y 432 | LP002377,Female,No,1,Graduate,Yes,8624,0,150,360,1,Semiurban,Y 433 | LP002379,Male,No,0,Graduate,No,6500,0,105,360,0,Rural,N 434 | LP002386,Male,No,0,Graduate,,12876,0,405,360,1,Semiurban,Y 435 | LP002387,Male,Yes,0,Graduate,No,2425,2340,143,360,1,Semiurban,Y 436 | LP002390,Male,No,0,Graduate,No,3750,0,100,360,1,Urban,Y 437 | LP002393,Female,,,Graduate,No,10047,0,,240,1,Semiurban,Y 438 | LP002398,Male,No,0,Graduate,No,1926,1851,50,360,1,Semiurban,Y 439 | LP002401,Male,Yes,0,Graduate,No,2213,1125,,360,1,Urban,Y 440 | LP002403,Male,No,0,Graduate,Yes,10416,0,187,360,0,Urban,N 441 | LP002407,Female,Yes,0,Not Graduate,Yes,7142,0,138,360,1,Rural,Y 442 | LP002408,Male,No,0,Graduate,No,3660,5064,187,360,1,Semiurban,Y 443 | LP002409,Male,Yes,0,Graduate,No,7901,1833,180,360,1,Rural,Y 444 | LP002418,Male,No,3+,Not Graduate,No,4707,1993,148,360,1,Semiurban,Y 445 | LP002422,Male,No,1,Graduate,No,37719,0,152,360,1,Semiurban,Y 446 | LP002424,Male,Yes,0,Graduate,No,7333,8333,175,300,,Rural,Y 447 | LP002429,Male,Yes,1,Graduate,Yes,3466,1210,130,360,1,Rural,Y 448 | LP002434,Male,Yes,2,Not Graduate,No,4652,0,110,360,1,Rural,Y 449 | LP002435,Male,Yes,0,Graduate,,3539,1376,55,360,1,Rural,N 450 | LP002443,Male,Yes,2,Graduate,No,3340,1710,150,360,0,Rural,N 451 | LP002444,Male,No,1,Not Graduate,Yes,2769,1542,190,360,,Semiurban,N 452 | LP002446,Male,Yes,2,Not Graduate,No,2309,1255,125,360,0,Rural,N 453 | LP002447,Male,Yes,2,Not Graduate,No,1958,1456,60,300,,Urban,Y 454 | LP002448,Male,Yes,0,Graduate,No,3948,1733,149,360,0,Rural,N 455 | LP002449,Male,Yes,0,Graduate,No,2483,2466,90,180,0,Rural,Y 456 | LP002453,Male,No,0,Graduate,Yes,7085,0,84,360,1,Semiurban,Y 457 | LP002455,Male,Yes,2,Graduate,No,3859,0,96,360,1,Semiurban,Y 458 | LP002459,Male,Yes,0,Graduate,No,4301,0,118,360,1,Urban,Y 459 | LP002467,Male,Yes,0,Graduate,No,3708,2569,173,360,1,Urban,N 460 | LP002472,Male,No,2,Graduate,No,4354,0,136,360,1,Rural,Y 461 | LP002473,Male,Yes,0,Graduate,No,8334,0,160,360,1,Semiurban,N 462 | LP002478,,Yes,0,Graduate,Yes,2083,4083,160,360,,Semiurban,Y 463 | LP002484,Male,Yes,3+,Graduate,No,7740,0,128,180,1,Urban,Y 464 | LP002487,Male,Yes,0,Graduate,No,3015,2188,153,360,1,Rural,Y 465 | LP002489,Female,No,1,Not Graduate,,5191,0,132,360,1,Semiurban,Y 466 | LP002493,Male,No,0,Graduate,No,4166,0,98,360,0,Semiurban,N 467 | LP002494,Male,No,0,Graduate,No,6000,0,140,360,1,Rural,Y 468 | LP002500,Male,Yes,3+,Not Graduate,No,2947,1664,70,180,0,Urban,N 469 | LP002501,,Yes,0,Graduate,No,16692,0,110,360,1,Semiurban,Y 470 | LP002502,Female,Yes,2,Not Graduate,,210,2917,98,360,1,Semiurban,Y 471 | LP002505,Male,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N 472 | LP002515,Male,Yes,1,Graduate,Yes,3450,2079,162,360,1,Semiurban,Y 473 | LP002517,Male,Yes,1,Not Graduate,No,2653,1500,113,180,0,Rural,N 474 | LP002519,Male,Yes,3+,Graduate,No,4691,0,100,360,1,Semiurban,Y 475 | LP002522,Female,No,0,Graduate,Yes,2500,0,93,360,,Urban,Y 476 | LP002524,Male,No,2,Graduate,No,5532,4648,162,360,1,Rural,Y 477 | LP002527,Male,Yes,2,Graduate,Yes,16525,1014,150,360,1,Rural,Y 478 | LP002529,Male,Yes,2,Graduate,No,6700,1750,230,300,1,Semiurban,Y 479 | LP002530,,Yes,2,Graduate,No,2873,1872,132,360,0,Semiurban,N 480 | LP002531,Male,Yes,1,Graduate,Yes,16667,2250,86,360,1,Semiurban,Y 481 | LP002533,Male,Yes,2,Graduate,No,2947,1603,,360,1,Urban,N 482 | LP002534,Female,No,0,Not Graduate,No,4350,0,154,360,1,Rural,Y 483 | LP002536,Male,Yes,3+,Not Graduate,No,3095,0,113,360,1,Rural,Y 484 | LP002537,Male,Yes,0,Graduate,No,2083,3150,128,360,1,Semiurban,Y 485 | LP002541,Male,Yes,0,Graduate,No,10833,0,234,360,1,Semiurban,Y 486 | LP002543,Male,Yes,2,Graduate,No,8333,0,246,360,1,Semiurban,Y 487 | LP002544,Male,Yes,1,Not Graduate,No,1958,2436,131,360,1,Rural,Y 488 | LP002545,Male,No,2,Graduate,No,3547,0,80,360,0,Rural,N 489 | LP002547,Male,Yes,1,Graduate,No,18333,0,500,360,1,Urban,N 490 | LP002555,Male,Yes,2,Graduate,Yes,4583,2083,160,360,1,Semiurban,Y 491 | LP002556,Male,No,0,Graduate,No,2435,0,75,360,1,Urban,N 492 | LP002560,Male,No,0,Not Graduate,No,2699,2785,96,360,,Semiurban,Y 493 | LP002562,Male,Yes,1,Not Graduate,No,5333,1131,186,360,,Urban,Y 494 | LP002571,Male,No,0,Not Graduate,No,3691,0,110,360,1,Rural,Y 495 | LP002582,Female,No,0,Not Graduate,Yes,17263,0,225,360,1,Semiurban,Y 496 | LP002585,Male,Yes,0,Graduate,No,3597,2157,119,360,0,Rural,N 497 | LP002586,Female,Yes,1,Graduate,No,3326,913,105,84,1,Semiurban,Y 498 | LP002587,Male,Yes,0,Not Graduate,No,2600,1700,107,360,1,Rural,Y 499 | LP002588,Male,Yes,0,Graduate,No,4625,2857,111,12,,Urban,Y 500 | LP002600,Male,Yes,1,Graduate,Yes,2895,0,95,360,1,Semiurban,Y 501 | LP002602,Male,No,0,Graduate,No,6283,4416,209,360,0,Rural,N 502 | LP002603,Female,No,0,Graduate,No,645,3683,113,480,1,Rural,Y 503 | LP002606,Female,No,0,Graduate,No,3159,0,100,360,1,Semiurban,Y 504 | LP002615,Male,Yes,2,Graduate,No,4865,5624,208,360,1,Semiurban,Y 505 | LP002618,Male,Yes,1,Not Graduate,No,4050,5302,138,360,,Rural,N 506 | LP002619,Male,Yes,0,Not Graduate,No,3814,1483,124,300,1,Semiurban,Y 507 | LP002622,Male,Yes,2,Graduate,No,3510,4416,243,360,1,Rural,Y 508 | LP002624,Male,Yes,0,Graduate,No,20833,6667,480,360,,Urban,Y 509 | LP002625,,No,0,Graduate,No,3583,0,96,360,1,Urban,N 510 | LP002626,Male,Yes,0,Graduate,Yes,2479,3013,188,360,1,Urban,Y 511 | LP002634,Female,No,1,Graduate,No,13262,0,40,360,1,Urban,Y 512 | LP002637,Male,No,0,Not Graduate,No,3598,1287,100,360,1,Rural,N 513 | LP002640,Male,Yes,1,Graduate,No,6065,2004,250,360,1,Semiurban,Y 514 | LP002643,Male,Yes,2,Graduate,No,3283,2035,148,360,1,Urban,Y 515 | LP002648,Male,Yes,0,Graduate,No,2130,6666,70,180,1,Semiurban,N 516 | LP002652,Male,No,0,Graduate,No,5815,3666,311,360,1,Rural,N 517 | LP002659,Male,Yes,3+,Graduate,No,3466,3428,150,360,1,Rural,Y 518 | LP002670,Female,Yes,2,Graduate,No,2031,1632,113,480,1,Semiurban,Y 519 | LP002682,Male,Yes,,Not Graduate,No,3074,1800,123,360,0,Semiurban,N 520 | LP002683,Male,No,0,Graduate,No,4683,1915,185,360,1,Semiurban,N 521 | LP002684,Female,No,0,Not Graduate,No,3400,0,95,360,1,Rural,N 522 | LP002689,Male,Yes,2,Not Graduate,No,2192,1742,45,360,1,Semiurban,Y 523 | LP002690,Male,No,0,Graduate,No,2500,0,55,360,1,Semiurban,Y 524 | LP002692,Male,Yes,3+,Graduate,Yes,5677,1424,100,360,1,Rural,Y 525 | LP002693,Male,Yes,2,Graduate,Yes,7948,7166,480,360,1,Rural,Y 526 | LP002697,Male,No,0,Graduate,No,4680,2087,,360,1,Semiurban,N 527 | LP002699,Male,Yes,2,Graduate,Yes,17500,0,400,360,1,Rural,Y 528 | LP002705,Male,Yes,0,Graduate,No,3775,0,110,360,1,Semiurban,Y 529 | LP002706,Male,Yes,1,Not Graduate,No,5285,1430,161,360,0,Semiurban,Y 530 | LP002714,Male,No,1,Not Graduate,No,2679,1302,94,360,1,Semiurban,Y 531 | LP002716,Male,No,0,Not Graduate,No,6783,0,130,360,1,Semiurban,Y 532 | LP002717,Male,Yes,0,Graduate,No,1025,5500,216,360,,Rural,Y 533 | LP002720,Male,Yes,3+,Graduate,No,4281,0,100,360,1,Urban,Y 534 | LP002723,Male,No,2,Graduate,No,3588,0,110,360,0,Rural,N 535 | LP002729,Male,No,1,Graduate,No,11250,0,196,360,,Semiurban,N 536 | LP002731,Female,No,0,Not Graduate,Yes,18165,0,125,360,1,Urban,Y 537 | LP002732,Male,No,0,Not Graduate,,2550,2042,126,360,1,Rural,Y 538 | LP002734,Male,Yes,0,Graduate,No,6133,3906,324,360,1,Urban,Y 539 | LP002738,Male,No,2,Graduate,No,3617,0,107,360,1,Semiurban,Y 540 | LP002739,Male,Yes,0,Not Graduate,No,2917,536,66,360,1,Rural,N 541 | LP002740,Male,Yes,3+,Graduate,No,6417,0,157,180,1,Rural,Y 542 | LP002741,Female,Yes,1,Graduate,No,4608,2845,140,180,1,Semiurban,Y 543 | LP002743,Female,No,0,Graduate,No,2138,0,99,360,0,Semiurban,N 544 | LP002753,Female,No,1,Graduate,,3652,0,95,360,1,Semiurban,Y 545 | LP002755,Male,Yes,1,Not Graduate,No,2239,2524,128,360,1,Urban,Y 546 | LP002757,Female,Yes,0,Not Graduate,No,3017,663,102,360,,Semiurban,Y 547 | LP002767,Male,Yes,0,Graduate,No,2768,1950,155,360,1,Rural,Y 548 | LP002768,Male,No,0,Not Graduate,No,3358,0,80,36,1,Semiurban,N 549 | LP002772,Male,No,0,Graduate,No,2526,1783,145,360,1,Rural,Y 550 | LP002776,Female,No,0,Graduate,No,5000,0,103,360,0,Semiurban,N 551 | LP002777,Male,Yes,0,Graduate,No,2785,2016,110,360,1,Rural,Y 552 | LP002778,Male,Yes,2,Graduate,Yes,6633,0,,360,0,Rural,N 553 | LP002784,Male,Yes,1,Not Graduate,No,2492,2375,,360,1,Rural,Y 554 | LP002785,Male,Yes,1,Graduate,No,3333,3250,158,360,1,Urban,Y 555 | LP002788,Male,Yes,0,Not Graduate,No,2454,2333,181,360,0,Urban,N 556 | LP002789,Male,Yes,0,Graduate,No,3593,4266,132,180,0,Rural,N 557 | LP002792,Male,Yes,1,Graduate,No,5468,1032,26,360,1,Semiurban,Y 558 | LP002794,Female,No,0,Graduate,No,2667,1625,84,360,,Urban,Y 559 | LP002795,Male,Yes,3+,Graduate,Yes,10139,0,260,360,1,Semiurban,Y 560 | LP002798,Male,Yes,0,Graduate,No,3887,2669,162,360,1,Semiurban,Y 561 | LP002804,Female,Yes,0,Graduate,No,4180,2306,182,360,1,Semiurban,Y 562 | LP002807,Male,Yes,2,Not Graduate,No,3675,242,108,360,1,Semiurban,Y 563 | LP002813,Female,Yes,1,Graduate,Yes,19484,0,600,360,1,Semiurban,Y 564 | LP002820,Male,Yes,0,Graduate,No,5923,2054,211,360,1,Rural,Y 565 | LP002821,Male,No,0,Not Graduate,Yes,5800,0,132,360,1,Semiurban,Y 566 | LP002832,Male,Yes,2,Graduate,No,8799,0,258,360,0,Urban,N 567 | LP002833,Male,Yes,0,Not Graduate,No,4467,0,120,360,,Rural,Y 568 | LP002836,Male,No,0,Graduate,No,3333,0,70,360,1,Urban,Y 569 | LP002837,Male,Yes,3+,Graduate,No,3400,2500,123,360,0,Rural,N 570 | LP002840,Female,No,0,Graduate,No,2378,0,9,360,1,Urban,N 571 | LP002841,Male,Yes,0,Graduate,No,3166,2064,104,360,0,Urban,N 572 | LP002842,Male,Yes,1,Graduate,No,3417,1750,186,360,1,Urban,Y 573 | LP002847,Male,Yes,,Graduate,No,5116,1451,165,360,0,Urban,N 574 | LP002855,Male,Yes,2,Graduate,No,16666,0,275,360,1,Urban,Y 575 | LP002862,Male,Yes,2,Not Graduate,No,6125,1625,187,480,1,Semiurban,N 576 | LP002863,Male,Yes,3+,Graduate,No,6406,0,150,360,1,Semiurban,N 577 | LP002868,Male,Yes,2,Graduate,No,3159,461,108,84,1,Urban,Y 578 | LP002872,,Yes,0,Graduate,No,3087,2210,136,360,0,Semiurban,N 579 | LP002874,Male,No,0,Graduate,No,3229,2739,110,360,1,Urban,Y 580 | LP002877,Male,Yes,1,Graduate,No,1782,2232,107,360,1,Rural,Y 581 | LP002888,Male,No,0,Graduate,,3182,2917,161,360,1,Urban,Y 582 | LP002892,Male,Yes,2,Graduate,No,6540,0,205,360,1,Semiurban,Y 583 | LP002893,Male,No,0,Graduate,No,1836,33837,90,360,1,Urban,N 584 | LP002894,Female,Yes,0,Graduate,No,3166,0,36,360,1,Semiurban,Y 585 | LP002898,Male,Yes,1,Graduate,No,1880,0,61,360,,Rural,N 586 | LP002911,Male,Yes,1,Graduate,No,2787,1917,146,360,0,Rural,N 587 | LP002912,Male,Yes,1,Graduate,No,4283,3000,172,84,1,Rural,N 588 | LP002916,Male,Yes,0,Graduate,No,2297,1522,104,360,1,Urban,Y 589 | LP002917,Female,No,0,Not Graduate,No,2165,0,70,360,1,Semiurban,Y 590 | LP002925,,No,0,Graduate,No,4750,0,94,360,1,Semiurban,Y 591 | LP002926,Male,Yes,2,Graduate,Yes,2726,0,106,360,0,Semiurban,N 592 | LP002928,Male,Yes,0,Graduate,No,3000,3416,56,180,1,Semiurban,Y 593 | LP002931,Male,Yes,2,Graduate,Yes,6000,0,205,240,1,Semiurban,N 594 | LP002933,,No,3+,Graduate,Yes,9357,0,292,360,1,Semiurban,Y 595 | LP002936,Male,Yes,0,Graduate,No,3859,3300,142,180,1,Rural,Y 596 | LP002938,Male,Yes,0,Graduate,Yes,16120,0,260,360,1,Urban,Y 597 | LP002940,Male,No,0,Not Graduate,No,3833,0,110,360,1,Rural,Y 598 | LP002941,Male,Yes,2,Not Graduate,Yes,6383,1000,187,360,1,Rural,N 599 | LP002943,Male,No,,Graduate,No,2987,0,88,360,0,Semiurban,N 600 | LP002945,Male,Yes,0,Graduate,Yes,9963,0,180,360,1,Rural,Y 601 | LP002948,Male,Yes,2,Graduate,No,5780,0,192,360,1,Urban,Y 602 | LP002949,Female,No,3+,Graduate,,416,41667,350,180,,Urban,N 603 | LP002950,Male,Yes,0,Not Graduate,,2894,2792,155,360,1,Rural,Y 604 | LP002953,Male,Yes,3+,Graduate,No,5703,0,128,360,1,Urban,Y 605 | LP002958,Male,No,0,Graduate,No,3676,4301,172,360,1,Rural,Y 606 | LP002959,Female,Yes,1,Graduate,No,12000,0,496,360,1,Semiurban,Y 607 | LP002960,Male,Yes,0,Not Graduate,No,2400,3800,,180,1,Urban,N 608 | LP002961,Male,Yes,1,Graduate,No,3400,2500,173,360,1,Semiurban,Y 609 | LP002964,Male,Yes,2,Not Graduate,No,3987,1411,157,360,1,Rural,Y 610 | LP002974,Male,Yes,0,Graduate,No,3232,1950,108,360,1,Rural,Y 611 | LP002978,Female,No,0,Graduate,No,2900,0,71,360,1,Rural,Y 612 | LP002979,Male,Yes,3+,Graduate,No,4106,0,40,180,1,Rural,Y 613 | LP002983,Male,Yes,1,Graduate,No,8072,240,253,360,1,Urban,Y 614 | LP002984,Male,Yes,2,Graduate,No,7583,0,187,360,1,Urban,Y 615 | LP002990,Female,No,0,Graduate,Yes,4583,0,133,360,0,Semiurban,N -------------------------------------------------------------------------------- /PR/Datasets/beer.txt: -------------------------------------------------------------------------------- 1 | name calories sodium alcohol cost 2 | Budweiser 144 15 4.7 0.43 3 | Schlitz 151 19 4.9 0.43 4 | Lowenbrau 157 15 0.9 0.48 5 | Kronenbourg 170 7 5.2 0.73 6 | Heineken 152 11 5.0 0.77 7 | Old_Milwaukee 145 23 4.6 0.28 8 | Augsberger 175 24 5.5 0.40 9 | Srohs_Bohemian_Style 149 27 4.7 0.42 10 | Miller_Lite 99 10 4.3 0.43 11 | Budweiser_Light 113 8 3.7 0.40 12 | Coors 140 18 4.6 0.44 13 | Coors_Light 102 15 4.1 0.46 14 | Michelob_Light 135 11 4.2 0.50 15 | Becks 150 19 4.7 0.76 16 | Kirin 149 6 5.0 0.79 17 | Pabst_Extra_Light 68 15 2.3 0.38 18 | Hamms 139 19 4.4 0.43 19 | Heilemans_Old_Style 144 24 4.9 0.43 20 | Olympia_Goled_Light 72 6 2.9 0.46 21 | Schlitz_Light 97 7 4.2 0.47 22 | -------------------------------------------------------------------------------- /PR/Datasets/heart.csv: -------------------------------------------------------------------------------- 1 | age sex cp trestbps chol fbs restecg thalach exang oldpeak slope ca thal target 2 | 63 1 3 145 233 1 0 150 0 2.3 0 0 1 1 3 | 37 1 2 130 250 0 1 187 0 3.5 0 0 2 1 4 | 41 0 1 130 204 0 0 172 0 1.4 2 0 2 1 5 | 56 1 1 120 236 0 1 178 0 0.8 2 0 2 1 6 | 57 0 0 120 354 0 1 163 1 0.6 2 0 2 1 7 | 57 1 0 140 192 0 1 148 0 0.4 1 0 1 1 8 | 56 0 1 140 294 0 0 153 0 1.3 1 0 2 1 9 | 44 1 1 120 263 0 1 173 0 0 2 0 3 1 10 | 52 1 2 172 199 1 1 162 0 0.5 2 0 3 1 11 | 57 1 2 150 168 0 1 174 0 1.6 2 0 2 1 12 | 54 1 0 140 239 0 1 160 0 1.2 2 0 2 1 13 | 48 0 2 130 275 0 1 139 0 0.2 2 0 2 1 14 | 49 1 1 130 266 0 1 171 0 0.6 2 0 2 1 15 | 64 1 3 110 211 0 0 144 1 1.8 1 0 2 1 16 | 58 0 3 150 283 1 0 162 0 1 2 0 2 1 17 | 50 0 2 120 219 0 1 158 0 1.6 1 0 2 1 18 | 58 0 2 120 340 0 1 172 0 0 2 0 2 1 19 | 66 0 3 150 226 0 1 114 0 2.6 0 0 2 1 20 | 43 1 0 150 247 0 1 171 0 1.5 2 0 2 1 21 | 69 0 3 140 239 0 1 151 0 1.8 2 2 2 1 22 | 59 1 0 135 234 0 1 161 0 0.5 1 0 3 1 23 | 44 1 2 130 233 0 1 179 1 0.4 2 0 2 1 24 | 42 1 0 140 226 0 1 178 0 0 2 0 2 1 25 | 61 1 2 150 243 1 1 137 1 1 1 0 2 1 26 | 40 1 3 140 199 0 1 178 1 1.4 2 0 3 1 27 | 71 0 1 160 302 0 1 162 0 0.4 2 2 2 1 28 | 59 1 2 150 212 1 1 157 0 1.6 2 0 2 1 29 | 51 1 2 110 175 0 1 123 0 0.6 2 0 2 1 30 | 65 0 2 140 417 1 0 157 0 0.8 2 1 2 1 31 | 53 1 2 130 197 1 0 152 0 1.2 0 0 2 1 32 | 41 0 1 105 198 0 1 168 0 0 2 1 2 1 33 | 65 1 0 120 177 0 1 140 0 0.4 2 0 3 1 34 | 44 1 1 130 219 0 0 188 0 0 2 0 2 1 35 | 54 1 2 125 273 0 0 152 0 0.5 0 1 2 1 36 | 51 1 3 125 213 0 0 125 1 1.4 2 1 2 1 37 | 46 0 2 142 177 0 0 160 1 1.4 0 0 2 1 38 | 54 0 2 135 304 1 1 170 0 0 2 0 2 1 39 | 54 1 2 150 232 0 0 165 0 1.6 2 0 3 1 40 | 65 0 2 155 269 0 1 148 0 0.8 2 0 2 1 41 | 65 0 2 160 360 0 0 151 0 0.8 2 0 2 1 42 | 51 0 2 140 308 0 0 142 0 1.5 2 1 2 1 43 | 48 1 1 130 245 0 0 180 0 0.2 1 0 2 1 44 | 45 1 0 104 208 0 0 148 1 3 1 0 2 1 45 | 53 0 0 130 264 0 0 143 0 0.4 1 0 2 1 46 | 39 1 2 140 321 0 0 182 0 0 2 0 2 1 47 | 52 1 1 120 325 0 1 172 0 0.2 2 0 2 1 48 | 44 1 2 140 235 0 0 180 0 0 2 0 2 1 49 | 47 1 2 138 257 0 0 156 0 0 2 0 2 1 50 | 53 0 2 128 216 0 0 115 0 0 2 0 0 1 51 | 53 0 0 138 234 0 0 160 0 0 2 0 2 1 52 | 51 0 2 130 256 0 0 149 0 0.5 2 0 2 1 53 | 66 1 0 120 302 0 0 151 0 0.4 1 0 2 1 54 | 62 1 2 130 231 0 1 146 0 1.8 1 3 3 1 55 | 44 0 2 108 141 0 1 175 0 0.6 1 0 2 1 56 | 63 0 2 135 252 0 0 172 0 0 2 0 2 1 57 | 52 1 1 134 201 0 1 158 0 0.8 2 1 2 1 58 | 48 1 0 122 222 0 0 186 0 0 2 0 2 1 59 | 45 1 0 115 260 0 0 185 0 0 2 0 2 1 60 | 34 1 3 118 182 0 0 174 0 0 2 0 2 1 61 | 57 0 0 128 303 0 0 159 0 0 2 1 2 1 62 | 71 0 2 110 265 1 0 130 0 0 2 1 2 1 63 | 54 1 1 108 309 0 1 156 0 0 2 0 3 1 64 | 52 1 3 118 186 0 0 190 0 0 1 0 1 1 65 | 41 1 1 135 203 0 1 132 0 0 1 0 1 1 66 | 58 1 2 140 211 1 0 165 0 0 2 0 2 1 67 | 35 0 0 138 183 0 1 182 0 1.4 2 0 2 1 68 | 51 1 2 100 222 0 1 143 1 1.2 1 0 2 1 69 | 45 0 1 130 234 0 0 175 0 0.6 1 0 2 1 70 | 44 1 1 120 220 0 1 170 0 0 2 0 2 1 71 | 62 0 0 124 209 0 1 163 0 0 2 0 2 1 72 | 54 1 2 120 258 0 0 147 0 0.4 1 0 3 1 73 | 51 1 2 94 227 0 1 154 1 0 2 1 3 1 74 | 29 1 1 130 204 0 0 202 0 0 2 0 2 1 75 | 51 1 0 140 261 0 0 186 1 0 2 0 2 1 76 | 43 0 2 122 213 0 1 165 0 0.2 1 0 2 1 77 | 55 0 1 135 250 0 0 161 0 1.4 1 0 2 1 78 | 51 1 2 125 245 1 0 166 0 2.4 1 0 2 1 79 | 59 1 1 140 221 0 1 164 1 0 2 0 2 1 80 | 52 1 1 128 205 1 1 184 0 0 2 0 2 1 81 | 58 1 2 105 240 0 0 154 1 0.6 1 0 3 1 82 | 41 1 2 112 250 0 1 179 0 0 2 0 2 1 83 | 45 1 1 128 308 0 0 170 0 0 2 0 2 1 84 | 60 0 2 102 318 0 1 160 0 0 2 1 2 1 85 | 52 1 3 152 298 1 1 178 0 1.2 1 0 3 1 86 | 42 0 0 102 265 0 0 122 0 0.6 1 0 2 1 87 | 67 0 2 115 564 0 0 160 0 1.6 1 0 3 1 88 | 68 1 2 118 277 0 1 151 0 1 2 1 3 1 89 | 46 1 1 101 197 1 1 156 0 0 2 0 3 1 90 | 54 0 2 110 214 0 1 158 0 1.6 1 0 2 1 91 | 58 0 0 100 248 0 0 122 0 1 1 0 2 1 92 | 48 1 2 124 255 1 1 175 0 0 2 2 2 1 93 | 57 1 0 132 207 0 1 168 1 0 2 0 3 1 94 | 52 1 2 138 223 0 1 169 0 0 2 4 2 1 95 | 54 0 1 132 288 1 0 159 1 0 2 1 2 1 96 | 45 0 1 112 160 0 1 138 0 0 1 0 2 1 97 | 53 1 0 142 226 0 0 111 1 0 2 0 3 1 98 | 62 0 0 140 394 0 0 157 0 1.2 1 0 2 1 99 | 52 1 0 108 233 1 1 147 0 0.1 2 3 3 1 100 | 43 1 2 130 315 0 1 162 0 1.9 2 1 2 1 101 | 53 1 2 130 246 1 0 173 0 0 2 3 2 1 102 | 42 1 3 148 244 0 0 178 0 0.8 2 2 2 1 103 | 59 1 3 178 270 0 0 145 0 4.2 0 0 3 1 104 | 63 0 1 140 195 0 1 179 0 0 2 2 2 1 105 | 42 1 2 120 240 1 1 194 0 0.8 0 0 3 1 106 | 50 1 2 129 196 0 1 163 0 0 2 0 2 1 107 | 68 0 2 120 211 0 0 115 0 1.5 1 0 2 1 108 | 69 1 3 160 234 1 0 131 0 0.1 1 1 2 1 109 | 45 0 0 138 236 0 0 152 1 0.2 1 0 2 1 110 | 50 0 1 120 244 0 1 162 0 1.1 2 0 2 1 111 | 50 0 0 110 254 0 0 159 0 0 2 0 2 1 112 | 64 0 0 180 325 0 1 154 1 0 2 0 2 1 113 | 57 1 2 150 126 1 1 173 0 0.2 2 1 3 1 114 | 64 0 2 140 313 0 1 133 0 0.2 2 0 3 1 115 | 43 1 0 110 211 0 1 161 0 0 2 0 3 1 116 | 55 1 1 130 262 0 1 155 0 0 2 0 2 1 117 | 37 0 2 120 215 0 1 170 0 0 2 0 2 1 118 | 41 1 2 130 214 0 0 168 0 2 1 0 2 1 119 | 56 1 3 120 193 0 0 162 0 1.9 1 0 3 1 120 | 46 0 1 105 204 0 1 172 0 0 2 0 2 1 121 | 46 0 0 138 243 0 0 152 1 0 1 0 2 1 122 | 64 0 0 130 303 0 1 122 0 2 1 2 2 1 123 | 59 1 0 138 271 0 0 182 0 0 2 0 2 1 124 | 41 0 2 112 268 0 0 172 1 0 2 0 2 1 125 | 54 0 2 108 267 0 0 167 0 0 2 0 2 1 126 | 39 0 2 94 199 0 1 179 0 0 2 0 2 1 127 | 34 0 1 118 210 0 1 192 0 0.7 2 0 2 1 128 | 47 1 0 112 204 0 1 143 0 0.1 2 0 2 1 129 | 67 0 2 152 277 0 1 172 0 0 2 1 2 1 130 | 52 0 2 136 196 0 0 169 0 0.1 1 0 2 1 131 | 74 0 1 120 269 0 0 121 1 0.2 2 1 2 1 132 | 54 0 2 160 201 0 1 163 0 0 2 1 2 1 133 | 49 0 1 134 271 0 1 162 0 0 1 0 2 1 134 | 42 1 1 120 295 0 1 162 0 0 2 0 2 1 135 | 41 1 1 110 235 0 1 153 0 0 2 0 2 1 136 | 41 0 1 126 306 0 1 163 0 0 2 0 2 1 137 | 49 0 0 130 269 0 1 163 0 0 2 0 2 1 138 | 60 0 2 120 178 1 1 96 0 0 2 0 2 1 139 | 62 1 1 128 208 1 0 140 0 0 2 0 2 1 140 | 57 1 0 110 201 0 1 126 1 1.5 1 0 1 1 141 | 64 1 0 128 263 0 1 105 1 0.2 1 1 3 1 142 | 51 0 2 120 295 0 0 157 0 0.6 2 0 2 1 143 | 43 1 0 115 303 0 1 181 0 1.2 1 0 2 1 144 | 42 0 2 120 209 0 1 173 0 0 1 0 2 1 145 | 67 0 0 106 223 0 1 142 0 0.3 2 2 2 1 146 | 76 0 2 140 197 0 2 116 0 1.1 1 0 2 1 147 | 70 1 1 156 245 0 0 143 0 0 2 0 2 1 148 | 44 0 2 118 242 0 1 149 0 0.3 1 1 2 1 149 | 60 0 3 150 240 0 1 171 0 0.9 2 0 2 1 150 | 44 1 2 120 226 0 1 169 0 0 2 0 2 1 151 | 42 1 2 130 180 0 1 150 0 0 2 0 2 1 152 | 66 1 0 160 228 0 0 138 0 2.3 2 0 1 1 153 | 71 0 0 112 149 0 1 125 0 1.6 1 0 2 1 154 | 64 1 3 170 227 0 0 155 0 0.6 1 0 3 1 155 | 66 0 2 146 278 0 0 152 0 0 1 1 2 1 156 | 39 0 2 138 220 0 1 152 0 0 1 0 2 1 157 | 58 0 0 130 197 0 1 131 0 0.6 1 0 2 1 158 | 47 1 2 130 253 0 1 179 0 0 2 0 2 1 159 | 35 1 1 122 192 0 1 174 0 0 2 0 2 1 160 | 58 1 1 125 220 0 1 144 0 0.4 1 4 3 1 161 | 56 1 1 130 221 0 0 163 0 0 2 0 3 1 162 | 56 1 1 120 240 0 1 169 0 0 0 0 2 1 163 | 55 0 1 132 342 0 1 166 0 1.2 2 0 2 1 164 | 41 1 1 120 157 0 1 182 0 0 2 0 2 1 165 | 38 1 2 138 175 0 1 173 0 0 2 4 2 1 166 | 38 1 2 138 175 0 1 173 0 0 2 4 2 1 167 | 67 1 0 160 286 0 0 108 1 1.5 1 3 2 0 168 | 67 1 0 120 229 0 0 129 1 2.6 1 2 3 0 169 | 62 0 0 140 268 0 0 160 0 3.6 0 2 2 0 170 | 63 1 0 130 254 0 0 147 0 1.4 1 1 3 0 171 | 53 1 0 140 203 1 0 155 1 3.1 0 0 3 0 172 | 56 1 2 130 256 1 0 142 1 0.6 1 1 1 0 173 | 48 1 1 110 229 0 1 168 0 1 0 0 3 0 174 | 58 1 1 120 284 0 0 160 0 1.8 1 0 2 0 175 | 58 1 2 132 224 0 0 173 0 3.2 2 2 3 0 176 | 60 1 0 130 206 0 0 132 1 2.4 1 2 3 0 177 | 40 1 0 110 167 0 0 114 1 2 1 0 3 0 178 | 60 1 0 117 230 1 1 160 1 1.4 2 2 3 0 179 | 64 1 2 140 335 0 1 158 0 0 2 0 2 0 180 | 43 1 0 120 177 0 0 120 1 2.5 1 0 3 0 181 | 57 1 0 150 276 0 0 112 1 0.6 1 1 1 0 182 | 55 1 0 132 353 0 1 132 1 1.2 1 1 3 0 183 | 65 0 0 150 225 0 0 114 0 1 1 3 3 0 184 | 61 0 0 130 330 0 0 169 0 0 2 0 2 0 185 | 58 1 2 112 230 0 0 165 0 2.5 1 1 3 0 186 | 50 1 0 150 243 0 0 128 0 2.6 1 0 3 0 187 | 44 1 0 112 290 0 0 153 0 0 2 1 2 0 188 | 60 1 0 130 253 0 1 144 1 1.4 2 1 3 0 189 | 54 1 0 124 266 0 0 109 1 2.2 1 1 3 0 190 | 50 1 2 140 233 0 1 163 0 0.6 1 1 3 0 191 | 41 1 0 110 172 0 0 158 0 0 2 0 3 0 192 | 51 0 0 130 305 0 1 142 1 1.2 1 0 3 0 193 | 58 1 0 128 216 0 0 131 1 2.2 1 3 3 0 194 | 54 1 0 120 188 0 1 113 0 1.4 1 1 3 0 195 | 60 1 0 145 282 0 0 142 1 2.8 1 2 3 0 196 | 60 1 2 140 185 0 0 155 0 3 1 0 2 0 197 | 59 1 0 170 326 0 0 140 1 3.4 0 0 3 0 198 | 46 1 2 150 231 0 1 147 0 3.6 1 0 2 0 199 | 67 1 0 125 254 1 1 163 0 0.2 1 2 3 0 200 | 62 1 0 120 267 0 1 99 1 1.8 1 2 3 0 201 | 65 1 0 110 248 0 0 158 0 0.6 2 2 1 0 202 | 44 1 0 110 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0 1 3 1 0 250 | 54 1 1 192 283 0 0 195 0 0 2 1 3 0 251 | 69 1 2 140 254 0 0 146 0 2 1 3 3 0 252 | 51 1 0 140 298 0 1 122 1 4.2 1 3 3 0 253 | 43 1 0 132 247 1 0 143 1 0.1 1 4 3 0 254 | 62 0 0 138 294 1 1 106 0 1.9 1 3 2 0 255 | 67 1 0 100 299 0 0 125 1 0.9 1 2 2 0 256 | 59 1 3 160 273 0 0 125 0 0 2 0 2 0 257 | 45 1 0 142 309 0 0 147 1 0 1 3 3 0 258 | 58 1 0 128 259 0 0 130 1 3 1 2 3 0 259 | 50 1 0 144 200 0 0 126 1 0.9 1 0 3 0 260 | 62 0 0 150 244 0 1 154 1 1.4 1 0 2 0 261 | 38 1 3 120 231 0 1 182 1 3.8 1 0 3 0 262 | 66 0 0 178 228 1 1 165 1 1 1 2 3 0 263 | 52 1 0 112 230 0 1 160 0 0 2 1 2 0 264 | 53 1 0 123 282 0 1 95 1 2 1 2 3 0 265 | 63 0 0 108 269 0 1 169 1 1.8 1 2 2 0 266 | 54 1 0 110 206 0 0 108 1 0 1 1 2 0 267 | 66 1 0 112 212 0 0 132 1 0.1 2 1 2 0 268 | 55 0 0 180 327 0 2 117 1 3.4 1 0 2 0 269 | 49 1 2 118 149 0 0 126 0 0.8 2 3 2 0 270 | 54 1 0 122 286 0 0 116 1 3.2 1 2 2 0 271 | 56 1 0 130 283 1 0 103 1 1.6 0 0 3 0 272 | 46 1 0 120 249 0 0 144 0 0.8 2 0 3 0 273 | 61 1 3 134 234 0 1 145 0 2.6 1 2 2 0 274 | 67 1 0 120 237 0 1 71 0 1 1 0 2 0 275 | 58 1 0 100 234 0 1 156 0 0.1 2 1 3 0 276 | 47 1 0 110 275 0 0 118 1 1 1 1 2 0 277 | 52 1 0 125 212 0 1 168 0 1 2 2 3 0 278 | 58 1 0 146 218 0 1 105 0 2 1 1 3 0 279 | 57 1 1 124 261 0 1 141 0 0.3 2 0 3 0 280 | 58 0 1 136 319 1 0 152 0 0 2 2 2 0 281 | 61 1 0 138 166 0 0 125 1 3.6 1 1 2 0 282 | 42 1 0 136 315 0 1 125 1 1.8 1 0 1 0 283 | 52 1 0 128 204 1 1 156 1 1 1 0 0 0 284 | 59 1 2 126 218 1 1 134 0 2.2 1 1 1 0 285 | 40 1 0 152 223 0 1 181 0 0 2 0 3 0 286 | 61 1 0 140 207 0 0 138 1 1.9 2 1 3 0 287 | 46 1 0 140 311 0 1 120 1 1.8 1 2 3 0 288 | 59 1 3 134 204 0 1 162 0 0.8 2 2 2 0 289 | 57 1 1 154 232 0 0 164 0 0 2 1 2 0 290 | 57 1 0 110 335 0 1 143 1 3 1 1 3 0 291 | 55 0 0 128 205 0 2 130 1 2 1 1 3 0 292 | 61 1 0 148 203 0 1 161 0 0 2 1 3 0 293 | 58 1 0 114 318 0 2 140 0 4.4 0 3 1 0 294 | 58 0 0 170 225 1 0 146 1 2.8 1 2 1 0 295 | 67 1 2 152 212 0 0 150 0 0.8 1 0 3 0 296 | 44 1 0 120 169 0 1 144 1 2.8 0 0 1 0 297 | 63 1 0 140 187 0 0 144 1 4 2 2 3 0 298 | 63 0 0 124 197 0 1 136 1 0 1 0 2 0 299 | 59 1 0 164 176 1 0 90 0 1 1 2 1 0 300 | 57 0 0 140 241 0 1 123 1 0.2 1 0 3 0 301 | 45 1 3 110 264 0 1 132 0 1.2 1 0 3 0 302 | 68 1 0 144 193 1 1 141 0 3.4 1 2 3 0 303 | 57 1 0 130 131 0 1 115 1 1.2 1 1 3 0 304 | 57 0 1 130 236 0 0 174 0 0 1 1 2 0 305 | -------------------------------------------------------------------------------- /PR/Datasets/training_data.csv: -------------------------------------------------------------------------------- 1 | X1,X2,X3,y 2 | 458.7,295.2,477,1187 3 | 488.5,326.5,497,1149.1 4 | 588.3,395.4,586.4,1268.3 5 | 613.3,440.6,606.1,1124.9 6 | 606.7,420,605.8,1194.5 7 | 574.7,388.6,589.8,1225.5 8 | 601.8,377.7,609.5,1244.6 9 | 761.8,419.7,718.5,1456.3 10 | 927,436.1,817.9,1646.1 11 | 750,402.9,718.2,1636 12 | 693.2,406.9,682.6,1458 13 | 753.3,373.9,685.1,1429.3 14 | 697.2,364.2,665.6,1506.2 15 | 757.5,402.1,708.5,1679.5 16 | 732.3,404.9,717.3,1842.6 17 | 887.6,550.1,871,2161.8 18 | 761,446.2,761.7,1779.5 19 | 691.2,440.9,736.3,1689.3 20 | 636.8,433.9,705.2,1755.6 21 | 662.1,460.6,731.5,1817.1 22 | 584.4,392.6,626.2,1456.6 23 | 630.9,408.2,628.9,1519.8 24 | 874.1,660.6,885.8,1886.4 25 | 1045.7,686.6,1000.9,1888.6 26 | 1011.6,681.7,1003.5,1791.5 27 | 878.5,588.7,860.1,1564.7 28 | 803.9,538.1,781.6,1362.5 29 | 777.2,564.2,800,1361.3 30 | 706.8,489.7,730.3,1186.2 31 | 601,403.5,613.3,957.8 32 | 592.6,384.2,588.4,882.6 33 | 534.2,341,525.8,873.6 34 | 530,346.1,516.8,834.6 35 | 413.3,284.1,444.2,721.6 36 | 394.9,224.1,406.5,702.4 37 | 342,197.4,361.2,628 38 | 378.7,231.9,398,680.5 39 | 362.7,223.9,380.6,642.2 40 | 367,234.2,387.1,681.8 41 | 336.4,213.9,362,618.8 42 | 274.9,175,298,498.6 43 | 265.3,176.7,285.5,474.3 44 | 283.6,183,301.4,492.5 45 | 229.5,148.9,253.7,434.7 46 | 304.2,207.8,323.8,517.3 47 | 348,231.6,371.4,643.8 48 | 329.5,263,352.6,573.2 49 | 304.9,247.1,338.4,615.8 50 | 301.1,254.7,338.2,632.8 51 | 302.6,258.9,340.4,631.2 52 | 289.2,269.3,339.7,641.4 53 | 298.1,245.8,318.9,549.3 54 | 286.3,253.8,315.8,525.6 55 | 266.7,237.1,296.7,491.8 56 | 267.9,241.2,294.2,457.7 57 | 291.7,252.6,313.5,490.9 58 | 310.7,258.5,327.3,537.1 59 | 321.1,242.8,329,546.1 60 | 309.1,213.8,310.4,510 61 | 298.8,206.7,301.6,502 62 | 247.2,175.9,254.4,414.9 63 | 255.1,185.1,262,414.7 64 | 250.8,185.6,258.2,401 65 | 222.3,163.8,232.2,369.4 66 | 394.4,304.5,406.7,604.5 67 | 411.8,319.8,427.5,645.9 68 | 388.1,321.5,412.2,617.3 69 | 522,424.2,542.6,765.5 70 | 523.9,440.2,558.1,800.8 71 | 624.5,516.9,658.5,959.8 72 | 707.2,567.2,735.7,1057.3 73 | 803.7,511,772.5,1087.3 74 | 661,429.1,645,963.8 75 | 729,478.6,708.4,994.5 76 | 768.4,507,750.6,1078.8 77 | 1063.4,648.3,1008.1,1464 78 | 1489.8,1018.1,1461.1,2112.1 79 | 1569.1,1196.8,1637.1,2680.2 80 | 1359.7,1016.2,1473.1,2262.3 81 | 1103,836.4,1210.3,1799.9 82 | 856.9,762.8,941,1201.2 83 | 742.3,691.3,825.6,1119.9 84 | 757.6,638.8,838.9,1088.9 85 | 684.1,555.4,741.4,930.3 86 | 687.4,555.9,725.9,953.2 87 | 568.3,456.2,613.3,848.4 88 | 542.3,416.2,569.6,811.6 89 | 518.5,402.1,539.8,757.3 90 | 634.8,517.5,670.2,932.9 91 | 667.3,526.9,689.2,971.2 92 | 650,506.7,675.1,992.4 93 | 587.7,455.4,614.2,934.6 94 | 574.4,456.3,598.4,884.7 95 | 491.6,396.3,516.4,766.4 96 | 464.9,368.3,484.2,712.6 97 | 437.3,343.8,454.6,679.6 98 | 444.6,341.5,460.7,689 99 | 481.4,361,486.5,728.7 100 | 518.6,386.7,515.3,762.1 101 | 690.1,526.7,697.3,1057.3 102 | 775.6,607.4,795.8,1171.8 103 | 644.3,492,660.2,957.4 104 | 717.7,532.8,724.2,1090.1 105 | 622.6,472.2,637.1,951.1 106 | 566.5,416.2,573.2,859.4 107 | 566.5,422.5,570.7,876.7 108 | 648.8,476.7,645.4,1015.2 109 | 563.9,425.6,586.2,953.8 110 | 540,414.4,566.4,906.1 111 | 501.9,380.9,531.9,847.2 112 | 504.1,369.2,533.7,842.4 113 | 473.1,354.5,499.9,781.2 114 | 450.7,326.8,468.9,720.9 115 | 456.4,324.1,465.7,699.3 116 | 413.8,305.1,422.9,604.6 117 | 421.2,310.1,433,637 118 | 434.2,321.9,442.9,642.3 119 | 439.3,326.8,454.6,659 120 | 392.5,293.4,409,609 121 | 354.8,299.3,387.8,577.7 122 | 383.3,288.2,400,605.2 123 | 344,249.3,358.9,539.6 124 | 336.6,246,350.8,511.9 125 | 333.1,244.1,333.8,500.4 126 | 330,239.6,333.7,519.4 127 | 378.1,272.5,380.7,595.1 128 | 420.5,299.9,422,667.8 129 | 413,277.2,411,687.2 130 | 484.3,324.1,474.6,812 131 | 475,310.4,458.2,810.7 132 | 439.4,296.7,430.3,769.7 133 | 473.1,323.3,462.1,816.1 134 | 498.3,340.8,504.3,879.4 135 | 547.6,374.8,540.3,964.1 136 | 634.3,445.5,624,1055.6 137 | 635.4,432.3,651.6,1327.6 138 | 345.9,248.6,363.2,668.8 139 | 374.9,252.1,382.8,691.8 140 | 351.3,236.5,363.1,661.8 141 | 360.7,227,364.4,679.9 142 | 347.4,216.6,351.8,649.1 143 | 370.4,232,377.8,698.7 144 | 328.2,202.3,337.6,636.8 145 | 347.8,202,344.3,618 146 | 315.8,189.9,318.8,579.9 147 | 329.8,211.1,336.2,594.6 148 | 363.6,237,354.2,643.5 149 | 342.6,219.5,337.6,634.3 150 | 370.8,247.8,362.4,639.9 151 | 371.7,253.2,362.7,598.3 152 | 349.8,226.3,336.1,553.6 153 | 335.1,221.2,337.7,610.7 154 | 312.3,205.9,316,583.7 155 | 372.2,247.5,371.4,693 156 | 415.8,275.3,418,809.2 157 | -------------------------------------------------------------------------------- /PR/New Text Document.txt: -------------------------------------------------------------------------------- 1 | new 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Machine-learning-Projects 🖥🖥 2 | The best way to get started with learning machine learning is to implement beginner to advanced level machine learning projects 🤖 3 | 4 | ![image](https://www.vippng.com/png/full/258-2589914_how-to-become-a-machine-learning-engineer-ai.png) 5 | 6 | 7 |

8 | 9 | ## How to select algorithms for Machine Learning Problems :: [click here](https://docs.microsoft.com/en-us/azure/machine-learning/media/algorithm-cheat-sheet/machine-learning-algorithm-cheat-sheet.svg) 10 | ![](https://docs.microsoft.com/en-us/azure/machine-learning/media/how-to-select-algorithms/how-to-select-algorithms.png) 11 | 12 | [ML Chaeatsheet](https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-science-pdf-f22dc900d2d7) 13 | 14 |

15 | 16 | 17 | 18 | # List of ML projects 💌 19 | 20 | - [x] **simple Linear Regression ML Model** [click here ](https://github.com/Aj7t/Machine-learning-Projects/tree/main/Blogathon) 21 | - [x] **Emogify Using Deep Learning Model** [click here ](https://github.com/Aj7t/Emogify) 22 | - [x] **Logistic Regression** [click here](https://github.com/Aj7t/Machine-learning-Projects/tree/main/Loan%20Prediction) 23 | - [x] **k-nearest neighbors algo** [Click here](https://github.com/Aj7t/Machine-learning-Projects/tree/main/KNN%20Implementation) 24 | - [x] **House-price Prediciton** [click here](https://github.com/Aj7t/Machine-learning-Projects/tree/main/House-price%20Prediciton) 25 | 26 | 27 | 28 |

29 | 30 | ## Resources 🚀🚀 31 | [![image](https://user-images.githubusercontent.com/67835881/117100205-cd86ee00-ad90-11eb-992f-9e7d7e3e558e.png)](https://learn.datacamp.com/) [![image](https://user-images.githubusercontent.com/67835881/117104060-193d9580-ad99-11eb-9e0c-78fdbe4ff490.png)](https://www.coursera.org/learn/machine-learning) [![image](https://user-images.githubusercontent.com/67835881/117100715-11c6be00-ad92-11eb-82da-16b2a7fe53cf.png)](https://courses.analyticsvidhya.com/) 32 | 33 |
34 | 35 | - youTube [here](https://www.youtube.com/user/krishnaik06/playlists) 36 | - Microsoft [here](https://docs.microsoft.com/en-us/azure/machine-learning/) 37 | --------------------------------------------------------------------------------