├── .gitignore ├── Diabetes_model.ipynb ├── LICENSE ├── README.md ├── Standarized_iris.ipynb └── tensorflow.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. 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-------------------------------------------------------------------------------- 1 | # tensorflow -------------------------------------------------------------------------------- /Standarized_iris.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "provenance": [], 7 | "authorship_tag": "ABX9TyPkG+7fYdRPK+ZbQKOZTwIw", 8 | "include_colab_link": true 9 | }, 10 | "kernelspec": { 11 | "name": "python3", 12 | "display_name": "Python 3" 13 | }, 14 | "language_info": { 15 | "name": "python" 16 | } 17 | }, 18 | "cells": [ 19 | { 20 | "cell_type": "markdown", 21 | "metadata": { 22 | "id": "view-in-github", 23 | "colab_type": "text" 24 | }, 25 | "source": [ 26 | "\"Open" 27 | ] 28 | }, 29 | { 30 | "cell_type": "code", 31 | "execution_count": 35, 32 | "metadata": { 33 | "id": "AqIIMMtyMEpV" 34 | }, 35 | "outputs": [], 36 | "source": [ 37 | "import tensorflow as tf\n", 38 | "import numpy as np\n", 39 | "import seaborn as sns\n", 40 | "import matplotlib.pyplot as plt\n", 41 | "from sklearn.datasets import load_iris\n", 42 | "from sklearn.preprocessing import StandardScaler\n", 43 | "from sklearn.metrics import accuracy_score\n", 44 | "from sklearn.model_selection import train_test_split\n", 45 | "from mlxtend.plotting import plot_decision_regions" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "source": [ 51 | "iris=load_iris()\n", 52 | "iris" 53 | ], 54 | "metadata": { 55 | "colab": { 56 | "base_uri": "https://localhost:8080/" 57 | }, 58 | "id": "GUQEbA_BMkZT", 59 | "outputId": "cdd59dfe-23a9-4139-fc8b-81fe54a4ee38" 60 | }, 61 | "execution_count": 11, 62 | "outputs": [ 63 | { 64 | "output_type": "execute_result", 65 | "data": { 66 | "text/plain": [ 67 | "{'data': array([[5.1, 3.5, 1.4, 0.2],\n", 68 | " [4.9, 3. , 1.4, 0.2],\n", 69 | " [4.7, 3.2, 1.3, 0.2],\n", 70 | " [4.6, 3.1, 1.5, 0.2],\n", 71 | " [5. , 3.6, 1.4, 0.2],\n", 72 | " [5.4, 3.9, 1.7, 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191 | " [6.7, 3.3, 5.7, 2.1],\n", 192 | " [7.2, 3.2, 6. , 1.8],\n", 193 | " [6.2, 2.8, 4.8, 1.8],\n", 194 | " [6.1, 3. , 4.9, 1.8],\n", 195 | " [6.4, 2.8, 5.6, 2.1],\n", 196 | " [7.2, 3. , 5.8, 1.6],\n", 197 | " [7.4, 2.8, 6.1, 1.9],\n", 198 | " [7.9, 3.8, 6.4, 2. ],\n", 199 | " [6.4, 2.8, 5.6, 2.2],\n", 200 | " [6.3, 2.8, 5.1, 1.5],\n", 201 | " [6.1, 2.6, 5.6, 1.4],\n", 202 | " [7.7, 3. , 6.1, 2.3],\n", 203 | " [6.3, 3.4, 5.6, 2.4],\n", 204 | " [6.4, 3.1, 5.5, 1.8],\n", 205 | " [6. , 3. , 4.8, 1.8],\n", 206 | " [6.9, 3.1, 5.4, 2.1],\n", 207 | " [6.7, 3.1, 5.6, 2.4],\n", 208 | " [6.9, 3.1, 5.1, 2.3],\n", 209 | " [5.8, 2.7, 5.1, 1.9],\n", 210 | " [6.8, 3.2, 5.9, 2.3],\n", 211 | " [6.7, 3.3, 5.7, 2.5],\n", 212 | " [6.7, 3. , 5.2, 2.3],\n", 213 | " [6.3, 2.5, 5. , 1.9],\n", 214 | " [6.5, 3. , 5.2, 2. ],\n", 215 | " [6.2, 3.4, 5.4, 2.3],\n", 216 | " [5.9, 3. , 5.1, 1.8]]),\n", 217 | " 'target': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", 218 | " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", 219 | " 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", 220 | " 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", 221 | " 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", 222 | " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", 223 | " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]),\n", 224 | " 'frame': None,\n", 225 | " 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='0.5).astype(\"int32\")\n" 410 | ], 411 | "metadata": { 412 | "colab": { 413 | "base_uri": "https://localhost:8080/" 414 | }, 415 | "id": "z-OTeO5BQZ6T", 416 | "outputId": "f654c28b-adc1-401b-f80d-cc187d7e396b" 417 | }, 418 | "execution_count": 23, 419 | "outputs": [ 420 | { 421 | "output_type": "stream", 422 | "name": "stdout", 423 | "text": [ 424 | "1/1 [==============================] - 0s 29ms/step\n" 425 | ] 426 | } 427 | ] 428 | }, 429 | { 430 | "cell_type": "code", 431 | "source": [ 432 | "accuracy=accuracy_score(y_test,y_pred)" 433 | ], 434 | "metadata": { 435 | "id": "llExgo1kQ0ej" 436 | }, 437 | "execution_count": 24, 438 | "outputs": [] 439 | }, 440 | { 441 | "cell_type": "code", 442 | "source": [ 443 | "print(\"Test Accuracy:{:.2f}%\".format(accuracy*100))" 444 | ], 445 | "metadata": { 446 | "colab": { 447 | "base_uri": "https://localhost:8080/" 448 | }, 449 | "id": "RjiVYMhgREEE", 450 | "outputId": "d5c54d09-6fce-4551-c272-e232e6f38b62" 451 | }, 452 | "execution_count": 25, 453 | "outputs": [ 454 | { 455 | "output_type": "stream", 456 | "name": "stdout", 457 | "text": [ 458 | "Test Accuracy:100.00%\n" 459 | ] 460 | } 461 | ] 462 | }, 463 | { 464 | "cell_type": "code", 465 | "source": [ 466 | "sns.scatterplot(x=x_train[:,0],y=x_train[:,1],hue=y_train,palette='Set1')\n", 467 | "plt.title(\"Iris Dataset-Standarized Features\")\n", 468 | "plt.xlabel('Feature 1(standardized)')\n", 469 | "plt.ylabel('Feature 2(standardized)')" 470 | ], 471 | "metadata": { 472 | "colab": { 473 | "base_uri": "https://localhost:8080/", 474 | "height": 489 475 | }, 476 | "id": "WT6G6tLZRWeh", 477 | "outputId": "c4febd3a-3190-4d5d-a6b9-986bfc9e89e9" 478 | }, 479 | "execution_count": 33, 480 | "outputs": [ 481 | { 482 | "output_type": "execute_result", 483 | "data": { 484 | "text/plain": [ 485 | "Text(0, 0.5, 'Feature 2(standardized)')" 486 | ] 487 | }, 488 | "metadata": {}, 489 | "execution_count": 33 490 | }, 491 | { 492 | "output_type": "display_data", 493 | "data": { 494 | "text/plain": [ 495 | "
" 496 | ], 497 | "image/png": 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\n" 498 | }, 499 | "metadata": {} 500 | } 501 | ] 502 | }, 503 | { 504 | "cell_type": "code", 505 | "source": [ 506 | "plot_decision_regions(x_train,y_train,clf=model,legend=2)\n", 507 | "plt.title(\"Decision Boundary of the Trained Neural Network\")\n", 508 | "plt.xlabel('Feature 1(standardized)')\n", 509 | "plt.ylabel('Feature 2(standardized)')" 510 | ], 511 | "metadata": { 512 | "colab": { 513 | "base_uri": "https://localhost:8080/", 514 | "height": 507 515 | }, 516 | "id": "CWjPuNYPTygq", 517 | "outputId": "c88e7b03-77cd-425f-d405-35b26c328c2f" 518 | }, 519 | "execution_count": 37, 520 | "outputs": [ 521 | { 522 | "output_type": "stream", 523 | "name": "stdout", 524 | "text": [ 525 | "9600/9600 [==============================] - 12s 1ms/step\n" 526 | ] 527 | }, 528 | { 529 | "output_type": "execute_result", 530 | "data": { 531 | "text/plain": [ 532 | "Text(0, 0.5, 'Feature 2(standardized)')" 533 | ] 534 | }, 535 | "metadata": {}, 536 | "execution_count": 37 537 | }, 538 | { 539 | "output_type": "display_data", 540 | "data": { 541 | "text/plain": [ 542 | "
" 543 | ], 544 | "image/png": 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\n" 545 | }, 546 | "metadata": {} 547 | } 548 | ] 549 | } 550 | ] 551 | } --------------------------------------------------------------------------------