├── APP development lab
    ├── Program2
    │   ├── AndroidManifest.xml
    │   ├── HomeActivity.java
    │   ├── README.md
    │   ├── activity_home.xml
    │   └── activity_main.xml
    ├── output
    │   ├── program1
    │   │   └── applab.pdf
    │   └── program2
    │   │   └── output2.png
    ├── program1
    │   └── activity_main.xml
    ├── program3
    │   ├── MainActivity.java
    │   └── activity_main.xml
    ├── program4
    │   ├── MainActivity.java
    │   └── activity_main.xml
    ├── program5
    │   ├── MainActivity.java
    │   └── activity_main.xml
    ├── program6
    │   ├── DBHelper.java
    │   ├── MainActivity.java
    │   └── activity_main.xml
    ├── program7
    │   ├── MainActivity.java
    │   └── activity_main.xml
    ├── program8
    │   ├── MainActivity.java
    │   └── activity_main.xml
    └── program9
    │   ├── GameView.java
    │   ├── MainActivity.java
    │   └── activity_main.xml
├── DIP
    ├── outputs
    │   ├── output1.png
    │   ├── output10.png
    │   ├── output2 .png
    │   ├── output3.png
    │   ├── output4.png
    │   ├── output5.png
    │   ├── output6.png
    │   ├── output7.png
    │   ├── output8-a.png
    │   ├── output8-b.png
    │   └── output9.png
    ├── program1.m
    ├── program10.m
    ├── program2.m
    ├── program3.m
    ├── program4.m
    ├── program5.m
    ├── program6.m
    ├── program7.m
    ├── program8.m
    └── program9.m
├── ML lab
    ├── mydata
    │   ├── Find_s_data.csv
    │   ├── candidate_data.csv
    │   ├── data.csv
    │   └── tennis.csv
    ├── program1(introduction)
    │   └── ml lab.pdf
    ├── program10.ipynb
    ├── program2.ipynb
    ├── program3.ipynb
    ├── program4.ipynb
    ├── program5.ipynb
    ├── program6.ipynb
    ├── program7.ipynb
    ├── program8.ipynb
    └── program9.ipynb
├── Python lab
    ├── new.c
    ├── program01.py
    ├── program02-a.py
    ├── program02-b.py
    ├── program03-a.py
    ├── program03-b.py
    ├── program04-a.py
    ├── program04-b.py
    ├── program04-c.py
    ├── program05-a.py
    ├── program05-b.py
    ├── program06-a.py
    ├── program06-b.py
    ├── program07.py
    ├── program08-a.py
    ├── program08-b.py
    ├── program09-a.py
    ├── program09-b.py
    ├── program10-a.py
    ├── program10-b.py
    ├── pythonlab.pdf
    └── test.txt
└── README.md


/APP development lab/Program2/AndroidManifest.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <manifest xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     xmlns:tools="http://schemas.android.com/tools">
 4 | 
 5 |     <application
 6 |         android:allowBackup="true"
 7 |         android:dataExtractionRules="@xml/data_extraction_rules"
 8 |         android:fullBackupContent="@xml/backup_rules"
 9 |         android:icon="@mipmap/ic_launcher"
10 |         android:label="@string/app_name"
11 |         android:roundIcon="@mipmap/ic_launcher_round"
12 |         android:supportsRtl="true"
13 |         android:theme="@style/Theme.Program2"
14 |         tools:targetApi="31">
15 | 
16 |         <!-- Main Activity - Launches the login screen -->
17 |         <activity
18 |             android:name=".MainActivity"
19 |             android:label="Login"
20 |             android:exported="true">
21 |             <intent-filter>
22 |                 <action android:name="android.intent.action.MAIN" />
23 |                 <category android:name="android.intent.category.LAUNCHER" />
24 |             </intent-filter>
25 |         </activity>
26 | 
27 |         <!-- Home Activity - The screen the user sees after login -->
28 |         <activity
29 |             android:name=".HomeActivity"
30 |             android:label="Home"
31 |             android:exported="true">
32 |         </activity>
33 | 
34 |     </application>
35 | 
36 | </manifest>
37 | 


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/APP development lab/Program2/HomeActivity.java:
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 1 | package com.example.program2;
 2 | 
 3 | 
 4 | import android.os.Bundle;
 5 | import android.widget.TextView;
 6 | import androidx.appcompat.app.AppCompatActivity;
 7 | 
 8 | public class HomeActivity extends AppCompatActivity {
 9 | 
10 |     @Override
11 |     protected void onCreate(Bundle savedInstanceState) {
12 |         super.onCreate(savedInstanceState);
13 |         setContentView(R.layout.activity_home);
14 | 
15 |         TextView tvWelcome = findViewById(R.id.tvWelcome);
16 |         tvWelcome.setText("Login Successful \n Welcome to the Home Page!");
17 |     }
18 | }
19 | 


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/APP development lab/Program2/README.md:
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 1 | ## AIM : To understand Activity, Intent, Create sample application with login module.(Check username and password).
 2 | 
 3 | ### **Understanding Activity, Intent, and Login Module in Android**  
 4 | 
 5 | #### **Activity**  
 6 | An **Activity** represents a single screen in an Android application. It acts as the main entry point for user interaction. Every app has at least one activity, usually `MainActivity`, which is launched when the app starts.  
 7 | 
 8 | #### **Intent**  
 9 | An **Intent** is used to navigate between activities or pass data between them. It can be **explicit** (for launching a specific activity within the app) or **implicit** (for launching system applications like the camera or browser).  
10 | 
11 | #### **Login Module**  
12 | A **Login Module** allows users to enter their credentials (username and password) and verifies them before granting access. It ensures security and can be implemented using static checks, local databases, or authentication APIs (e.g., Firebase).  
13 | 
14 | In our sample application, we created a **simple login module** where:  
15 | 1. The user enters a **username and password**.  
16 | 2. The credentials are validated in the `MainActivity`.  
17 | 3. A message is displayed based on the verification result.  
18 | 
19 | This demonstrates the basic functionality of activities, intents, and UI interaction in Android development. 🚀


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/APP development lab/Program2/activity_home.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:gravity="center"
 6 |     android:orientation="vertical"
 7 |     android:padding="20dp">
 8 | 
 9 |     <TextView
10 |         android:id="@+id/tvWelcome"
11 |         android:layout_width="wrap_content"
12 |         android:layout_height="wrap_content"
13 |         android:text="Welcome to the Home Page!"
14 |         android:textSize="24sp"
15 |         android:textColor="#000000"/>
16 | </LinearLayout>
17 | 


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/APP development lab/Program2/activity_main.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:orientation="vertical"
 6 |     android:gravity="center"
 7 |     android:padding="20dp">
 8 | 
 9 |     <TextView
10 |         android:id="@+id/tvHeading"
11 |         android:layout_width="wrap_content"
12 |         android:layout_height="wrap_content"
13 |         android:text="Login Form"
14 |         android:textSize="24sp"
15 |         android:textColor="@color/black"
16 |         android:textStyle="bold"
17 |         android:paddingBottom="20dp" />
18 | 
19 | 
20 |     <EditText
21 |         android:id="@+id/etUsername"
22 |         android:layout_width="match_parent"
23 |         android:layout_height="wrap_content"
24 |         android:hint="Username"
25 |         android:inputType="text" />
26 | 
27 |     <!-- Password EditText -->
28 |     <EditText
29 |         android:id="@+id/etPassword"
30 |         android:layout_width="match_parent"
31 |         android:layout_height="wrap_content"
32 |         android:hint="Password"
33 |         android:inputType="textPassword" />
34 | 
35 |     <!-- Login Button -->
36 |     <Button
37 |         android:id="@+id/btnLogin"
38 |         android:layout_width="match_parent"
39 |         android:layout_height="wrap_content"
40 |         android:text="Login" />
41 | 
42 |     <!-- Message TextView -->
43 |     <TextView
44 |         android:id="@+id/tvMessage"
45 |         android:layout_width="wrap_content"
46 |         android:layout_height="wrap_content"
47 |         android:text=""
48 |         android:textSize="18sp"
49 |         android:textColor="#FF0000"
50 |         android:paddingTop="10dp"/>
51 | </LinearLayout>
52 | 


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/APP development lab/output/program1/applab.pdf:
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https://raw.githubusercontent.com/Niraj-Ramnani/Lab-Record-6th-sem/333ed742d31d32b8c3e384d6dd4875e6c204ee81/APP development lab/output/program1/applab.pdf


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/APP development lab/output/program2/output2.png:
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https://raw.githubusercontent.com/Niraj-Ramnani/Lab-Record-6th-sem/333ed742d31d32b8c3e384d6dd4875e6c204ee81/APP development lab/output/program2/output2.png


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/APP development lab/program1/activity_main.xml:
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1 | <TextView
2 |     android:layout_width="wrap_content"
3 |     android:layout_height="wrap_content"
4 |     android:text="Hello, World!"
5 |     android:textSize="24sp"
6 |     android:layout_gravity="center"/>
7 | 


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/APP development lab/program3/MainActivity.java:
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 1 | package com.example.program2;
 2 | 
 3 | import android.content.Intent;
 4 | import android.os.Bundle;
 5 | import android.view.View;
 6 | import android.widget.*;
 7 | 
 8 | import androidx.appcompat.app.AppCompatActivity;
 9 | 
10 | public class MainActivity extends AppCompatActivity {
11 | 
12 |     @Override
13 |     protected void onCreate(Bundle savedInstanceState) {
14 |         super.onCreate(savedInstanceState);
15 |         setContentView(R.layout.activity_main);
16 | 
17 |         // References to the views
18 |         EditText etUsername = findViewById(R.id.etUsername);
19 |         EditText etPassword = findViewById(R.id.etPassword);
20 |         Button btnLogin = findViewById(R.id.btnLogin);
21 |         TextView tvMessage = findViewById(R.id.tvMessage);
22 | 
23 |         // Set OnClickListener for the login button
24 |         btnLogin.setOnClickListener(new View.OnClickListener() {
25 |             @Override
26 |             public void onClick(View v) {
27 |                 // Get text from EditText fields
28 |                 String username = etUsername.getText().toString();
29 |                 String password = etPassword.getText().toString();
30 | 
31 |                 // Predefined username and password for login
32 |                 String correctUsername = "Niraj";
33 |                 String correctPassword = "2004";
34 | 
35 |                 // Check if the entered username and password match the predefined values
36 |                 if (username.equals(correctUsername) && password.equals(correctPassword)) {
37 |                     // Successful login, display success message and go to HomeActivity
38 |                     tvMessage.setText("Login Successful!");
39 |                     tvMessage.setTextColor(getResources().getColor(android.R.color.holo_green_dark));
40 | 
41 |                     // Create an Intent to move to the HomeActivity
42 |                     Intent intent = new Intent(MainActivity.this, HomeActivity.class);
43 |                     startActivity(intent);
44 |                     finish();  // Close the LoginActivity
45 |                 } else {
46 |                     // Invalid login, display error message
47 |                     tvMessage.setText("Invalid Username or Password!");
48 |                     tvMessage.setTextColor(getResources().getColor(android.R.color.holo_red_dark));
49 |                 }
50 |             }
51 |         });
52 |     }
53 | }


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/APP development lab/program3/activity_main.xml:
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 1 | package com.example.program3;
 2 | 
 3 | import android.os.Bundle;
 4 | import android.view.View;
 5 | import android.widget.Button;
 6 | import android.widget.EditText;
 7 | import androidx.appcompat.app.AppCompatActivity;
 8 | 
 9 | public class MainActivity extends AppCompatActivity {
10 |     private EditText etInput;
11 |     private String currentInput = "";
12 |     private String operator = "";
13 |     private double num1 = 0;
14 | 
15 |     @Override
16 |     protected void onCreate(Bundle savedInstanceState) {
17 |         super.onCreate(savedInstanceState);
18 |         setContentView(R.layout.activity_main);
19 | 
20 |         etInput = findViewById(R.id.etInput);
21 | 
22 |         int[] numButtons = {R.id.btn0, R.id.btn1, R.id.btn2, R.id.btn3, R.id.btn4, R.id.btn5, R.id.btn6, R.id.btn7, R.id.btn8, R.id.btn9};
23 |         int[] opButtons = {R.id.btnAdd, R.id.btnSub, R.id.btnMul, R.id.btnDiv};
24 | 
25 |         View.OnClickListener numClickListener = v -> {
26 |             Button b = (Button) v;
27 |             currentInput += b.getText().toString();
28 |             etInput.setText(currentInput);
29 |         };
30 | 
31 |         View.OnClickListener opClickListener = v -> {
32 |             if (!currentInput.isEmpty()) {
33 |                 num1 = Double.parseDouble(currentInput);
34 |                 Button b = (Button) v;
35 |                 operator = b.getText().toString();
36 |                 currentInput = "";
37 |                 etInput.setText("");
38 |             }
39 |         };
40 | 
41 |         for (int id : numButtons) findViewById(id).setOnClickListener(numClickListener);
42 |         for (int id : opButtons) findViewById(id).setOnClickListener(opClickListener);
43 | 
44 |         findViewById(R.id.btnEq).setOnClickListener(v -> {
45 |             if (!currentInput.isEmpty() && !operator.isEmpty()) {
46 |                 double num2 = Double.parseDouble(currentInput);
47 |                 double result = 0;
48 | 
49 |                 switch (operator) {
50 |                     case "+": result = num1 + num2; break;
51 |                     case "-": result = num1 - num2; break;
52 |                     case "*": result = num1 * num2; break;
53 |                     case "/": result = num2 != 0 ? num1 / num2 : 0; break;
54 |                 }
55 | 
56 |                 etInput.setText(String.valueOf(result));
57 |                 currentInput = String.valueOf(result);
58 |                 operator = "";
59 |             }
60 |         });
61 | 
62 |         findViewById(R.id.btnClear).setOnClickListener(v -> {
63 |             currentInput = "";
64 |             operator = "";
65 |             num1 = 0;
66 |             etInput.setText("");
67 |         });
68 |     }
69 | }


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/APP development lab/program4/MainActivity.java:
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 1 | package com.example.program4;
 2 | 
 3 | import android.os.AsyncTask;
 4 | import android.os.Bundle;
 5 | import android.util.Xml;
 6 | import android.widget.ArrayAdapter;
 7 | import android.widget.ListView;
 8 | import android.widget.Toast;
 9 | import androidx.appcompat.app.AppCompatActivity;
10 | import org.xmlpull.v1.XmlPullParser;
11 | import java.io.InputStream;
12 | import java.net.HttpURLConnection;
13 | import java.net.URL;
14 | import java.util.ArrayList;
15 | import java.util.List;
16 | 
17 | public class MainActivity extends AppCompatActivity {
18 |     private ListView lv;
19 |     private List<String> titles = new ArrayList<>();
20 |     private String rssUrl = "https://rss.nytimes.com/services/xml/rss/nyt/World.xml"; // RSS Feed URL
21 | 
22 |     @Override
23 |     protected void onCreate(Bundle savedInstanceState) {
24 |         super.onCreate(savedInstanceState);
25 |         setContentView(R.layout.activity_main);
26 | 
27 |         lv = findViewById(R.id.lv);
28 |         new FetchFeed().execute(rssUrl);
29 |     }
30 | 
31 |     private class FetchFeed extends AsyncTask<String, Void, List<String>> {
32 |         @Override
33 |         protected List<String> doInBackground(String... urls) {
34 |             try {
35 |                 URL url = new URL(urls[0]);
36 |                 HttpURLConnection conn = (HttpURLConnection) url.openConnection();
37 |                 conn.setRequestMethod("GET");
38 |                 conn.setConnectTimeout(5000); // Set timeout
39 |                 conn.setReadTimeout(5000);
40 | 
41 |                 if (conn.getResponseCode() == HttpURLConnection.HTTP_OK) {
42 |                     InputStream is = conn.getInputStream();
43 |                     return parseXML(is);
44 |                 } else {
45 |                     return null;
46 |                 }
47 |             } catch (Exception e) {
48 |                 e.printStackTrace();
49 |                 return null;
50 |             }
51 |         }
52 | 
53 |         @Override
54 |         protected void onPostExecute(List<String> result) {
55 |             if (result != null && !result.isEmpty()) {
56 |                 titles = result;
57 |                 ArrayAdapter<String> adapter = new ArrayAdapter<>(MainActivity.this, android.R.layout.simple_list_item_1, titles);
58 |                 lv.setAdapter(adapter);
59 |             } else {
60 |                 Toast.makeText(MainActivity.this, "Failed to load RSS feed", Toast.LENGTH_SHORT).show();
61 |             }
62 |         }
63 |     }
64 | 
65 |     private List<String> parseXML(InputStream is) throws Exception {
66 |         List<String> items = new ArrayList<>();
67 |         XmlPullParser p = Xml.newPullParser();
68 |         p.setInput(is, null);
69 |         boolean insideItem = false;
70 |         int eType;
71 | 
72 |         while ((eType = p.next()) != XmlPullParser.END_DOCUMENT) {
73 |             if (eType == XmlPullParser.START_TAG) {
74 |                 if (p.getName().equalsIgnoreCase("item")) {
75 |                     insideItem = true;
76 |                 } else if (insideItem && p.getName().equalsIgnoreCase("title")) {
77 |                     items.add(p.nextText());
78 |                 }
79 |             } else if (eType == XmlPullParser.END_TAG && p.getName().equalsIgnoreCase("item")) {
80 |                 insideItem = false;
81 |             }
82 |         }
83 |         return items;
84 |     }
85 | }
86 | 


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/APP development lab/program4/activity_main.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:orientation="vertical"
 6 |     android:padding="16dp"
 7 |     android:background="@android:color/white">
 8 | 
 9 |     <TextView
10 |         android:layout_width="wrap_content"
11 |         android:layout_height="wrap_content"
12 |         android:text="Latest RSS Feed"
13 |         android:textSize="22sp"
14 |         android:textStyle="bold"
15 |         android:textColor="@android:color/black"
16 |         android:layout_gravity="center"
17 |         android:paddingBottom="12dp"/>
18 | 
19 |     <ListView
20 |         android:id="@+id/lv"
21 |         android:layout_width="match_parent"
22 |         android:layout_height="match_parent"
23 |         android:divider="@android:color/darker_gray"
24 |         android:dividerHeight="1dp"
25 |         android:background="@android:color/white"/>
26 | 
27 | </LinearLayout>
28 | 


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/APP development lab/program5/MainActivity.java:
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 1 | package com.example.program5;
 2 | 
 3 | import android.os.Bundle;
 4 | import android.graphics.Canvas;
 5 | import android.graphics.Color;
 6 | import android.graphics.Paint;
 7 | import android.view.View;
 8 | import androidx.appcompat.app.AppCompatActivity;
 9 | 
10 | public class MainActivity extends AppCompatActivity {
11 |     @Override
12 |     protected void onCreate(Bundle savedInstanceState) {
13 |         super.onCreate(savedInstanceState);
14 | 
15 |         // Set content view to a custom View directly
16 |         setContentView(new View(this) {
17 |             private Paint p = new Paint();
18 | 
19 |             @Override
20 |             protected void onDraw(Canvas c) {
21 |                 super.onDraw(c);
22 | 
23 |                 // Set background color
24 |                 c.drawColor(Color.MAGENTA);
25 | 
26 |                 // Configure paint for filling
27 |                 p.setStyle(Paint.Style.FILL);
28 | 
29 |                 // Draw Line (Thicker, Filled Effect)
30 |                 p.setColor(Color.RED);
31 |                 p.setStrokeWidth(20);
32 |                 c.drawLine(100, 300, 600, 300, p);
33 | 
34 |                 // Draw First Rectangle (Filled)
35 |                 p.setColor(Color.GREEN);
36 |                 c.drawRect(200, 350, 400, 550, p);
37 | 
38 |                 // Draw Circle (Filled)
39 |                 p.setColor(Color.BLUE);
40 |                 c.drawCircle(350, 750, 120, p);
41 | 
42 |                 // Draw Second Rectangle (Filled)
43 |                 p.setColor(Color.CYAN);
44 |                 c.drawRect(100, 900, 600, 1100, p);
45 |             }
46 |         });
47 |     }
48 | }
49 | 


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/APP development lab/program5/activity_main.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:gravity="center"
 6 |     android:orientation="vertical"
 7 |     android:background="@android:color/darker_gray">
 8 | 
 9 |     <TextView
10 |         android:layout_width="wrap_content"
11 |         android:layout_height="wrap_content"
12 |         android:text="Drawing Shapes..."
13 |         android:textSize="20sp"
14 |         android:textStyle="bold"
15 |         android:textColor="@android:color/black"/>
16 | 
17 | </LinearLayout>
18 | 


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/APP development lab/program6/DBHelper.java:
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 1 | 
 2 | package com.example.program6;
 3 | 
 4 | import android.content.ContentValues;
 5 | import android.content.Context;
 6 | import android.database.Cursor;
 7 | import android.database.sqlite.SQLiteDatabase;
 8 | import android.database.sqlite.SQLiteOpenHelper;
 9 | import android.widget.Toast;
10 | 
11 | public class DBHelper extends SQLiteOpenHelper {
12 |     private static final String DB_NAME = "SchoolDB";
13 |     private static final int DB_VERSION = 1;
14 |     private static final String TABLE_NAME = "students";
15 |     private static final String COL_ID = "id";
16 |     private static final String COL_NAME = "name";
17 |     private static final String COL_CLASS = "class";
18 |     private static final String COL_MARKS = "marks";
19 |     private Context context;
20 | 
21 |     public DBHelper(Context context) {
22 |         super(context, DB_NAME, null, DB_VERSION);
23 |         this.context = context;
24 |     }
25 | 
26 |     @Override
27 |     public void onCreate(SQLiteDatabase db) {
28 |         String query = "CREATE TABLE " + TABLE_NAME + " (" +
29 |                 COL_ID + " INTEGER PRIMARY KEY AUTOINCREMENT, " +
30 |                 COL_NAME + " TEXT, " +
31 |                 COL_CLASS + " TEXT, " +
32 |                 COL_MARKS + " INTEGER);";
33 |         db.execSQL(query);
34 |     }
35 | 
36 |     @Override
37 |     public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {
38 |         db.execSQL("DROP TABLE IF EXISTS " + TABLE_NAME);
39 |         onCreate(db);
40 |     }
41 | 
42 |     public void insertStudent(String name, String studentClass, int marks) {
43 |         SQLiteDatabase db = this.getWritableDatabase();
44 |         ContentValues values = new ContentValues();
45 |         values.put(COL_NAME, name);
46 |         values.put(COL_CLASS, studentClass);
47 |         values.put(COL_MARKS, marks);
48 |         long result = db.insert(TABLE_NAME, null, values);
49 |         db.close();
50 |         if (result == -1) {
51 |             Toast.makeText(context, "Insert Failed", Toast.LENGTH_SHORT).show();
52 |         } else {
53 |             Toast.makeText(context, "Student Added", Toast.LENGTH_SHORT).show();
54 |         }
55 |     }
56 | 
57 |     public Cursor getStudents() {
58 |         SQLiteDatabase db = this.getReadableDatabase();
59 |         return db.rawQuery("SELECT * FROM " + TABLE_NAME, null);
60 |     }
61 | }
62 | 
63 | 


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/APP development lab/program6/MainActivity.java:
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 1 | package com.example.program6;
 2 | 
 3 | import android.database.Cursor;
 4 | import android.os.Bundle;
 5 | import android.view.View;
 6 | import android.widget.Button;
 7 | import android.widget.EditText;
 8 | import android.widget.ScrollView;
 9 | import android.widget.TextView;
10 | import androidx.appcompat.app.AppCompatActivity;
11 | 
12 | public class MainActivity extends AppCompatActivity {
13 |     private DBHelper dbHelper;
14 |     private EditText etName, etClass, etMarks;
15 |     private TextView tvResult;
16 |     private Button btnAdd, btnView;
17 |     private ScrollView scrollView;
18 | 
19 |     @Override
20 |     protected void onCreate(Bundle savedInstanceState) {
21 |         super.onCreate(savedInstanceState);
22 |         setContentView(R.layout.activity_main);
23 | 
24 |         dbHelper = new DBHelper(this);
25 |         etName = findViewById(R.id.etName);
26 |         etClass = findViewById(R.id.etClass);
27 |         etMarks = findViewById(R.id.etMarks);
28 |         tvResult = findViewById(R.id.tvResult);
29 |         btnAdd = findViewById(R.id.btnAdd);
30 |         btnView = findViewById(R.id.btnView);
31 |         scrollView = findViewById(R.id.scrollView);
32 | 
33 |         btnAdd.setOnClickListener(new View.OnClickListener() {
34 |             @Override
35 |             public void onClick(View v) {
36 |                 String name = etName.getText().toString();
37 |                 String studentClass = etClass.getText().toString();
38 |                 int marks = Integer.parseInt(etMarks.getText().toString());
39 |                 dbHelper.insertStudent(name, studentClass, marks);
40 |                 etName.setText("");
41 |                 etClass.setText("");
42 |                 etMarks.setText("");
43 |             }
44 |         });
45 | 
46 |         btnView.setOnClickListener(new View.OnClickListener() {
47 |             @Override
48 |             public void onClick(View v) {
49 |                 Cursor cursor = dbHelper.getStudents();
50 |                 StringBuilder sb = new StringBuilder();
51 |                 while (cursor.moveToNext()) {
52 |                     sb.append("ID: ").append(cursor.getInt(0))
53 |                             .append("\nName: ").append(cursor.getString(1))
54 |                             .append("\nClass: ").append(cursor.getString(2))
55 |                             .append("\nMarks: ").append(cursor.getInt(3))
56 |                             .append("\n----------------------\n");
57 |                 }
58 |                 cursor.close();
59 |                 tvResult.setText(sb.toString());
60 |                 scrollView.fullScroll(View.FOCUS_DOWN);
61 |             }
62 |         });
63 |     }
64 | }
65 | 


--------------------------------------------------------------------------------
/APP development lab/program6/activity_main.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:padding="20dp"
 6 |     android:orientation="vertical"
 7 |     android:gravity="center"
 8 |     android:background="@android:color/holo_blue_light">
 9 | 
10 |     <TextView
11 |         android:layout_width="wrap_content"
12 |         android:layout_height="wrap_content"
13 |         android:text="School Database Management"
14 |         android:textSize="22sp"
15 |         android:textStyle="bold"
16 |         android:textColor="@android:color/white"
17 |         android:paddingBottom="20dp"/>
18 | 
19 |     <EditText
20 |         android:id="@+id/etName"
21 |         android:layout_width="match_parent"
22 |         android:layout_height="wrap_content"
23 |         android:hint="Enter Student Name"
24 |         android:background="@android:color/white"
25 |         android:padding="10dp"/>
26 | 
27 |     <EditText
28 |         android:id="@+id/etClass"
29 |         android:layout_width="match_parent"
30 |         android:layout_height="wrap_content"
31 |         android:hint="Enter Class"
32 |         android:background="@android:color/white"
33 |         android:padding="10dp"/>
34 | 
35 |     <EditText
36 |         android:id="@+id/etMarks"
37 |         android:layout_width="match_parent"
38 |         android:layout_height="wrap_content"
39 |         android:hint="Enter Marks"
40 |         android:inputType="number"
41 |         android:background="@android:color/white"
42 |         android:padding="10dp"/>
43 | 
44 |     <Button
45 |         android:id="@+id/btnAdd"
46 |         android:layout_width="match_parent"
47 |         android:layout_height="wrap_content"
48 |         android:text="Add Student"
49 |         android:background="@android:color/holo_green_dark"
50 |         android:textColor="@android:color/white"
51 |         android:padding="10dp"/>
52 | 
53 |     <Button
54 |         android:id="@+id/btnView"
55 |         android:layout_width="match_parent"
56 |         android:layout_height="wrap_content"
57 |         android:text="View Students"
58 |         android:background="@android:color/holo_orange_dark"
59 |         android:textColor="@android:color/white"
60 |         android:padding="10dp"/>
61 | 
62 |     <ScrollView
63 |         android:id="@+id/scrollView"
64 |         android:layout_width="match_parent"
65 |         android:layout_height="wrap_content"
66 |         android:paddingTop="20dp">
67 | 
68 |         <TextView
69 |             android:id="@+id/tvResult"
70 |             android:layout_width="match_parent"
71 |             android:layout_height="wrap_content"
72 |             android:text="Student Records will be displayed here"
73 |             android:textSize="16sp"
74 |             android:textColor="@android:color/white"/>
75 |     </ScrollView>
76 | </LinearLayout>
77 | 


--------------------------------------------------------------------------------
/APP development lab/program7/MainActivity.java:
--------------------------------------------------------------------------------
 1 | package com.example.program7;
 2 | 
 3 | 
 4 | import android.Manifest;
 5 | import android.content.pm.PackageManager;
 6 | import android.location.Location;
 7 | import android.os.Bundle;
 8 | import android.widget.Button;
 9 | import android.widget.TextView;
10 | import android.widget.Toast;
11 | import androidx.annotation.NonNull;
12 | import androidx.appcompat.app.AppCompatActivity;
13 | import androidx.core.app.ActivityCompat;
14 | import com.google.android.gms.location.FusedLocationProviderClient;
15 | import com.google.android.gms.location.LocationServices;
16 | import com.google.android.gms.tasks.OnSuccessListener;
17 | 
18 | public class MainActivity extends AppCompatActivity {
19 |     private static final int LOCATION_PERMISSION_REQUEST_CODE = 1;
20 |     private FusedLocationProviderClient fusedLocationClient;
21 |     private TextView tvLocation;
22 |     private Button btnGetLocation;
23 | 
24 |     @Override
25 |     protected void onCreate(Bundle savedInstanceState) {
26 |         super.onCreate(savedInstanceState);
27 |         setContentView(R.layout.activity_main);
28 | 
29 |         tvLocation = findViewById(R.id.tvLocation);
30 |         btnGetLocation = findViewById(R.id.btnGetLocation);
31 |         fusedLocationClient = LocationServices.getFusedLocationProviderClient(this);
32 | 
33 |         btnGetLocation.setOnClickListener(v -> getLocation());
34 |     }
35 | 
36 |     private void getLocation() {
37 |         if (ActivityCompat.checkSelfPermission(this, Manifest.permission.ACCESS_FINE_LOCATION) != PackageManager.PERMISSION_GRANTED) {
38 |             ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.ACCESS_FINE_LOCATION}, LOCATION_PERMISSION_REQUEST_CODE);
39 |             return;
40 |         }
41 | 
42 |         fusedLocationClient.getLastLocation().addOnSuccessListener(new OnSuccessListener<Location>() {
43 |             @Override
44 |             public void onSuccess(Location location) {
45 |                 if (location != null) {
46 |                     double latitude = location.getLatitude();
47 |                     double longitude = location.getLongitude();
48 |                     tvLocation.setText("Latitude: " + latitude + "\nLongitude: " + longitude);
49 |                 } else {
50 |                     tvLocation.setText("Unable to fetch location.");
51 |                 }
52 |             }
53 |         });
54 |     }
55 | 
56 |     @Override
57 |     public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions, @NonNull int[] grantResults) {
58 |         super.onRequestPermissionsResult(requestCode, permissions, grantResults);
59 |         if (requestCode == LOCATION_PERMISSION_REQUEST_CODE) {
60 |             if (grantResults.length > 0 && grantResults[0] == PackageManager.PERMISSION_GRANTED) {
61 |                 getLocation();
62 |             } else {
63 |                 Toast.makeText(this, "Permission Denied!", Toast.LENGTH_SHORT).show();
64 |             }
65 |         }
66 |     }
67 | }
68 | 


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/APP development lab/program7/activity_main.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:padding="20dp"
 6 |     android:orientation="vertical"
 7 |     android:gravity="center"
 8 |     android:background="#F5F5F5">
 9 | 
10 |     <TextView
11 |         android:layout_width="wrap_content"
12 |         android:layout_height="wrap_content"
13 |         android:text="📍 GPS Location Finder"
14 |         android:textSize="22sp"
15 |         android:textStyle="bold"
16 |         android:textColor="#000000"
17 |         android:paddingBottom="15dp"/>
18 | 
19 |     <TextView
20 |         android:id="@+id/tvLocation"
21 |         android:layout_width="match_parent"
22 |         android:layout_height="wrap_content"
23 |         android:text="Your location will appear here"
24 |         android:textSize="18sp"
25 |         android:textColor="#333333"
26 |         android:padding="15dp"
27 |         android:background="#FFFFFF"
28 |         android:elevation="4dp"
29 |         android:gravity="center"
30 |         android:layout_marginBottom="20dp"/>
31 | 
32 |     <Button
33 |         android:id="@+id/btnGetLocation"
34 |         android:layout_width="match_parent"
35 |         android:layout_height="wrap_content"
36 |         android:text="Get Current Location"
37 |         android:textSize="16sp"
38 |         android:padding="10dp"
39 |         android:textColor="#FFFFFF"
40 |         android:background="#4CAF50"
41 |         android:layout_marginTop="10dp"/>
42 | 
43 | </LinearLayout>
44 | 


--------------------------------------------------------------------------------
/APP development lab/program8/MainActivity.java:
--------------------------------------------------------------------------------
  1 | package com.example.program8;
  2 | 
  3 | import android.Manifest;
  4 | import android.content.pm.PackageManager;
  5 | import android.os.Bundle;
  6 | import android.os.Environment;
  7 | import android.view.View;
  8 | import android.widget.Button;
  9 | import android.widget.EditText;
 10 | import android.widget.TextView;
 11 | import androidx.annotation.NonNull;
 12 | import androidx.appcompat.app.AppCompatActivity;
 13 | import androidx.core.app.ActivityCompat;
 14 | import androidx.core.content.ContextCompat;
 15 | import java.io.*;
 16 | 
 17 | public class MainActivity extends AppCompatActivity {
 18 |     private EditText etInput;
 19 |     private TextView tvOutput;
 20 |     private static final int PERMISSION_REQUEST_CODE = 100;
 21 | 
 22 |     @Override
 23 |     protected void onCreate(Bundle savedInstanceState) {
 24 |         super.onCreate(savedInstanceState);
 25 |         setContentView(R.layout.activity_main);
 26 | 
 27 |         etInput = findViewById(R.id.etInput);
 28 |         tvOutput = findViewById(R.id.tvOutput);
 29 |         Button btnWrite = findViewById(R.id.btnWrite);
 30 |         Button btnRead = findViewById(R.id.btnRead);
 31 | 
 32 |         // Request permissions
 33 |         if (ContextCompat.checkSelfPermission(this, Manifest.permission.WRITE_EXTERNAL_STORAGE)
 34 |                 != PackageManager.PERMISSION_GRANTED) {
 35 |             ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.WRITE_EXTERNAL_STORAGE},
 36 |                     PERMISSION_REQUEST_CODE);
 37 |         }
 38 | 
 39 |         // Write data to SD Card
 40 |         btnWrite.setOnClickListener(v -> writeToSDCard(etInput.getText().toString()));
 41 | 
 42 |         // Read data from SD Card
 43 |         btnRead.setOnClickListener(v -> readFromSDCard());
 44 |     }
 45 | 
 46 |     private void writeToSDCard(String data) {
 47 |         if (isExternalStorageWritable()) {
 48 |             File file = new File(getExternalFilesDir(null), "data.txt");
 49 |             try (FileOutputStream fos = new FileOutputStream(file);
 50 |                  OutputStreamWriter osw = new OutputStreamWriter(fos)) {
 51 |                 osw.write(data);
 52 |                 tvOutput.setText("Data written to: " + file.getAbsolutePath());
 53 |             } catch (IOException e) {
 54 |                 tvOutput.setText("Error writing file: " + e.getMessage());
 55 |             }
 56 |         } else {
 57 |             tvOutput.setText("SD Card not writable!");
 58 |         }
 59 |     }
 60 | 
 61 |     private void readFromSDCard() {
 62 |         if (isExternalStorageReadable()) {
 63 |             File file = new File(getExternalFilesDir(null), "data.txt");
 64 |             if (file.exists()) {
 65 |                 try (BufferedReader br = new BufferedReader(new FileReader(file))) {
 66 |                     StringBuilder sb = new StringBuilder();
 67 |                     String line;
 68 |                     while ((line = br.readLine()) != null) {
 69 |                         sb.append(line).append("\n");
 70 |                     }
 71 |                     tvOutput.setText("Read Data: \n" + sb.toString());
 72 |                 } catch (IOException e) {
 73 |                     tvOutput.setText("Error reading file: " + e.getMessage());
 74 |                 }
 75 |             } else {
 76 |                 tvOutput.setText("File does not exist!");
 77 |             }
 78 |         } else {
 79 |             tvOutput.setText("SD Card not readable!");
 80 |         }
 81 |     }
 82 | 
 83 |     private boolean isExternalStorageWritable() {
 84 |         return Environment.getExternalStorageState().equals(Environment.MEDIA_MOUNTED);
 85 |     }
 86 | 
 87 |     private boolean isExternalStorageReadable() {
 88 |         String state = Environment.getExternalStorageState();
 89 |         return state.equals(Environment.MEDIA_MOUNTED) || state.equals(Environment.MEDIA_MOUNTED_READ_ONLY);
 90 |     }
 91 | 
 92 |     @Override
 93 |     public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions, @NonNull int[] grantResults) {
 94 |         super.onRequestPermissionsResult(requestCode, permissions, grantResults);
 95 |         if (requestCode == PERMISSION_REQUEST_CODE) {
 96 |             if (grantResults.length > 0 && grantResults[0] != PackageManager.PERMISSION_GRANTED) {
 97 |                 tvOutput.setText("Permission Denied!");
 98 |             }
 99 |         }
100 |     }
101 | }
102 | 


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/APP development lab/program8/activity_main.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent"
 5 |     android:orientation="vertical"
 6 |     android:padding="16dp"
 7 |     android:gravity="center"
 8 |     android:background="@android:color/white">
 9 | 
10 |     <EditText
11 |         android:id="@+id/etInput"
12 |         android:layout_width="match_parent"
13 |         android:layout_height="wrap_content"
14 |         android:hint="Enter text"
15 |         android:padding="10dp"
16 |         android:background="@android:color/darker_gray"/>
17 | 
18 |     <Button
19 |         android:id="@+id/btnWrite"
20 |         android:layout_width="match_parent"
21 |         android:layout_height="wrap_content"
22 |         android:text="Write to SD Card"
23 |         android:background="@android:color/holo_blue_dark"
24 |         android:textColor="@android:color/white"
25 |         android:layout_marginTop="10dp"/>
26 | 
27 |     <Button
28 |         android:id="@+id/btnRead"
29 |         android:layout_width="match_parent"
30 |         android:layout_height="wrap_content"
31 |         android:text="Read from SD Card"
32 |         android:background="@android:color/holo_green_dark"
33 |         android:textColor="@android:color/white"
34 |         android:layout_marginTop="10dp"/>
35 | 
36 |     <TextView
37 |         android:id="@+id/tvOutput"
38 |         android:layout_width="match_parent"
39 |         android:layout_height="wrap_content"
40 |         android:textSize="16sp"
41 |         android:textColor="@android:color/black"
42 |         android:padding="10dp"
43 |         android:layout_marginTop="10dp"
44 |         android:background="@android:color/darker_gray"/>
45 | </LinearLayout>
46 | 


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/APP development lab/program9/GameView.java:
--------------------------------------------------------------------------------
  1 | package com.example.program9;
  2 | 
  3 | 
  4 | import android.content.Context;
  5 | import android.graphics.Canvas;
  6 | import android.graphics.Color;
  7 | import android.graphics.Paint;
  8 | import android.util.AttributeSet;
  9 | import android.view.MotionEvent;
 10 | import android.view.SurfaceHolder;
 11 | import android.view.SurfaceView;
 12 | 
 13 | public class GameView extends SurfaceView implements SurfaceHolder.Callback {
 14 |     private GameThread gameThread;
 15 |     private float ballX, ballY, ballRadius = 40, ballSpeedX = 15, ballSpeedY = -15; // Increased ball speed
 16 |     private float paddleX, paddleY, paddleWidth = 400, paddleHeight = 80; // Increased paddle size
 17 |     private int score = 0;
 18 |     private Paint ballPaint, paddlePaint, scorePaint;
 19 | 
 20 |     public GameView(Context context, AttributeSet attrs) {
 21 |         super(context, attrs);
 22 |         getHolder().addCallback(this);
 23 |         setFocusable(true);
 24 | 
 25 |         // Initialize paints
 26 |         ballPaint = new Paint();
 27 |         ballPaint.setColor(Color.RED);
 28 |         ballPaint.setStyle(Paint.Style.FILL);
 29 | 
 30 |         paddlePaint = new Paint();
 31 |         paddlePaint.setColor(Color.BLACK);
 32 |         paddlePaint.setStyle(Paint.Style.FILL);
 33 | 
 34 |         scorePaint = new Paint();
 35 |         scorePaint.setColor(Color.BLACK);
 36 |         scorePaint.setTextSize(50);
 37 |     }
 38 | 
 39 |     @Override
 40 |     public void surfaceCreated(SurfaceHolder holder) {
 41 |         // Initialize ball and paddle positions
 42 |         ballX = getWidth() / 2f;
 43 |         ballY = getHeight() / 2f;
 44 |         paddleX = getWidth() / 2f - paddleWidth / 2;
 45 |         paddleY = getHeight() - 180; // Moved paddle higher (closer to the top)
 46 | 
 47 |         // Start the game thread
 48 |         gameThread = new GameThread(this);
 49 |         gameThread.setRunning(true);
 50 |         gameThread.start();
 51 |     }
 52 | 
 53 |     @Override
 54 |     public void surfaceChanged(SurfaceHolder holder, int format, int width, int height) {}
 55 | 
 56 |     @Override
 57 |     public void surfaceDestroyed(SurfaceHolder holder) {
 58 |         boolean retry = true;
 59 |         gameThread.setRunning(false);
 60 |         while (retry) {
 61 |             try {
 62 |                 gameThread.join();
 63 |                 retry = false;
 64 |             } catch (InterruptedException e) {
 65 |                 e.printStackTrace();
 66 |             }
 67 |         }
 68 |     }
 69 | 
 70 |     public void update() {
 71 |         // Update ball position
 72 |         ballX += ballSpeedX;
 73 |         ballY += ballSpeedY;
 74 | 
 75 |         // Ball collision with walls
 76 |         if (ballX + ballRadius > getWidth() || ballX - ballRadius < 0) {
 77 |             ballSpeedX = -ballSpeedX;
 78 |         }
 79 |         if (ballY - ballRadius < 0) {
 80 |             ballSpeedY = -ballSpeedY;
 81 |             score++; // Increment score when ball hits the top
 82 |         }
 83 | 
 84 |         // Ball collision with paddle
 85 |         if (ballY + ballRadius > paddleY && ballY - ballRadius < paddleY + paddleHeight &&
 86 |                 ballX > paddleX && ballX < paddleX + paddleWidth) {
 87 |             ballSpeedY = -ballSpeedY;
 88 |         }
 89 | 
 90 |         // Game over if ball falls below paddle
 91 |         if (ballY + ballRadius > getHeight()) {
 92 |             ballX = getWidth() / 2f;
 93 |             ballY = getHeight() / 2f;
 94 |             ballSpeedX = 8; // Reset to new speed
 95 |             ballSpeedY = -8; // Reset to new speed
 96 |             score = 0; // Reset score
 97 |         }
 98 |     }
 99 | 
100 |     @Override
101 |     public void draw(Canvas canvas) {
102 |         super.draw(canvas);
103 |         if (canvas == null) return;
104 | 
105 |         // Clear the canvas
106 |         canvas.drawColor(Color.CYAN);
107 | 
108 |         // Draw the ball
109 |         canvas.drawCircle(ballX, ballY, ballRadius, ballPaint);
110 | 
111 |         // Draw the paddle
112 |         canvas.drawRect(paddleX, paddleY, paddleX + paddleWidth, paddleY + paddleHeight, paddlePaint);
113 | 
114 |         // Draw the score
115 |         canvas.drawText("Score: " + score, 20, 50, scorePaint);
116 |     }
117 | 
118 |     @Override
119 |     public boolean onTouchEvent(MotionEvent event) {
120 |         // Move paddle based on touch
121 |         if (event.getAction() == MotionEvent.ACTION_MOVE || event.getAction() == MotionEvent.ACTION_DOWN) {
122 |             paddleX = event.getX() - paddleWidth / 2;
123 |             // Keep paddle within bounds
124 |             if (paddleX < 0) paddleX = 0;
125 |             if (paddleX + paddleWidth > getWidth()) paddleX = getWidth() - paddleWidth;
126 |         }
127 |         return true;
128 |     }
129 | 
130 |     // Game thread class to handle game loop
131 |     private class GameThread extends Thread {
132 |         private SurfaceHolder surfaceHolder;
133 |         private GameView gameView;
134 |         private boolean running;
135 | 
136 |         public GameThread(GameView gameView) {
137 |             this.gameView = gameView;
138 |             this.surfaceHolder = gameView.getHolder();
139 |         }
140 | 
141 |         public void setRunning(boolean running) {
142 |             this.running = running;
143 |         }
144 | 
145 |         @Override
146 |         public void run() {
147 |             while (running) {
148 |                 Canvas canvas = null;
149 |                 try {
150 |                     canvas = surfaceHolder.lockCanvas();
151 |                     synchronized (surfaceHolder) {
152 |                         gameView.update();
153 |                         gameView.draw(canvas);
154 |                     }
155 |                 } finally {
156 |                     if (canvas != null) {
157 |                         surfaceHolder.unlockCanvasAndPost(canvas);
158 |                     }
159 |                 }
160 |                 try {
161 |                     Thread.sleep(16); // Aim for ~60 FPS
162 |                 } catch (InterruptedException e) {
163 |                     e.printStackTrace();
164 |                 }
165 |             }
166 |         }
167 |     }
168 | 
169 | }


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/APP development lab/program9/MainActivity.java:
--------------------------------------------------------------------------------
 1 | package com.example.program9;
 2 | 
 3 | 
 4 | import android.os.Bundle;
 5 | import androidx.appcompat.app.AppCompatActivity;
 6 | 
 7 | public class MainActivity extends AppCompatActivity {
 8 | 
 9 |     @Override
10 |     protected void onCreate(Bundle savedInstanceState) {
11 |         super.onCreate(savedInstanceState);
12 |         setContentView(R.layout.activity_main);
13 |     }
14 | }


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/APP development lab/program9/activity_main.xml:
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 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <RelativeLayout xmlns:android="http://schemas.android.com/apk/res/android"
 3 |     android:layout_width="match_parent"
 4 |     android:layout_height="match_parent">
 5 | 
 6 |     <com.example.program9.GameView
 7 |         android:id="@+id/gameView"
 8 |         android:layout_width="match_parent"
 9 |         android:layout_height="match_parent" />
10 | 
11 | </RelativeLayout>


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/DIP/outputs/output9.png:
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https://raw.githubusercontent.com/Niraj-Ramnani/Lab-Record-6th-sem/333ed742d31d32b8c3e384d6dd4875e6c204ee81/DIP/outputs/output9.png


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/DIP/program1.m:
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1 | // Write a program in matlab to read and display gray/images of different format 
2 | a = imread("cameraman.jpeg");
3 | a = imresize(a,[200,200]);
4 | imshow(a);
5 | b = imread("coloredChips.png");
6 | subplot(1,2,2);
7 | imshow(b);


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/DIP/program10.m:
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 1 | x = imread("office_2.jpg");
 2 | x1 = rgb2gray(x);
 3 | f1 = [1 1 1; 1 1 1; 1 1 1];
 4 | f2 = [2 2 2 ; 2 4 2; 2 2 2];
 5 | f3 = [-1 -1 -1 ; -1 -1 -1 ; -1 -1 -1 ];
 6 | subplot(2,2,1);
 7 | imshow(x),title("original");
 8 | subplot(2,2,2);
 9 | y1 = conv2(x1,f1);
10 | imshow(uint8(y1)),title("funnel 1");
11 | subplot(2,2,3);
12 | y2 = conv2(x1,f2);
13 | imshow(uint8(y2)),title("funnel 2");
14 | subplot(2,2,4);
15 | y3 = conv2(x1,f3);
16 | imshow(uint8(y3)),title("funnel 3");


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/DIP/program2.m:
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 1 | // Write a program to read a RGB image extract 3 colur components red , green , blue 
 2 | rgb = imread("coloredChips.png");
 3 | r = rgb;
 4 | g = rgb;
 5 | b = rgb;
 6 | r(:,:,2) = 0;
 7 | r(:,:,3) = 0;
 8 | g(:,:,1) = 0;
 9 | g(:,:,3) = 0;
10 | b(:,:,1) = 0;
11 | b(:,:,2) = 0;
12 | subplot(2,2,1);
13 | imshow(rgb) ,title('rgb image');
14 | subplot(2,2,2);
15 | imshow(r) ,title('red component');
16 | subplot(2,2,3);
17 | imshow(g) ,title('green component');
18 | subplot(2,2,4);
19 | imshow(b) ,title('blue component');


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/DIP/program3.m:
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 1 | // Write a program to perform arithmetic operations on RGB images 
 2 | i = imread ("coloredChips.png");
 3 | j = imread("fabric.png");
 4 | c = imresize(i,[200 200]);
 5 | d = imresize(j,[200 200]);
 6 | e = imadd(c,d);
 7 | f = imsubtract(c,d);
 8 | g = imdivide(c,d);
 9 | h = immultiply(c,d);
10 | subplot(3,2,1);
11 | imshow(c) , title("chips");
12 | subplot(3,2,2);
13 | imshow(d) , title("fabric");
14 | subplot(3,2,3);
15 | imshow(e) , title("additon");
16 | subplot(3,2,4);
17 | imshow(f) , title("substraction");
18 | 
19 | subplot(3,2,5);
20 | imshow(g) , title("multiplication");
21 | subplot(3,2,6);
22 | imshow(h) , title("division");


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/DIP/program4.m:
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 1 | // Write a program in matlab to find negative transform of an image 
 2 | clc;
 3 | close all;
 4 | I = imread("coloredChips.png");
 5 | I = rgb2gray(I);
 6 | [m n] = size(I);
 7 | for q = 1:n
 8 |     for p = 1:m
 9 |         I2(p , q) = 225 - I(p,q);
10 |     end
11 | end
12 | I1 = imread("coloredChips.png");
13 | subplot(2,1,1);
14 | imshow(I1),title('original');
15 | subplot(2,1,2);
16 | imshow(I2),title('negative');


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/DIP/program5.m:
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 1 | // Write a program in matlab to perform image scaling , rotation and translation
 2 | f = imread("coloredChips.png");
 3 | i = imtranslate(f,[15,25]);
 4 | j = imrotate(f,30);
 5 | k = imresize(f,0.5);
 6 | subplot(1,3,1);
 7 | imshow(i),title('translation');
 8 | subplot(1,3,2);
 9 | imshow(j),title('Rotation');
10 | subplot(1,3,3);
11 | imshow(k),title('Scaling');
12 | size(k)
13 | size(i)


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/DIP/program6.m:
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 1 | //
 2 | img = imread("office_2.jpg");
 3 | r = double(img);
 4 | c = 1;
 5 | s = c * log(1 + r);
 6 | t = 255/(c * log(256));
 7 | b = uint8(t * s);
 8 | subplot(1,2,1);
 9 | imshow(img),title('Normal image');
10 | subplot(1,2,2);
11 | imshow(b),title('Log transformation');


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/DIP/program7.m:
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 1 | img = imread('office_2.jpg');
 2 | r = double(img);
 3 | c = 1; 
 4 | subplot(4,2,1);
 5 | imshow(img);
 6 | title('Original Image');
 7 | 
 8 | gamma_values = [0.6, 0.4, 0.2, 2,4,6];
 9 | 
10 | for k = 1:length(gamma_values)
11 |     g = gamma_values(k);
12 |     
13 |  
14 |     s = c * (r .^ g);
15 |     t = 255/(c * (255 .^g));
16 |     o = uint8(t * s);
17 |     subplot(4,2,k+1);
18 |     imshow(o);
19 |     title(['Gamma = ', num2str(g)]);
20 | end


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/DIP/program8.m:
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 1 | sgtitle('Images ');
 2 | for i = 1:6
 3 |     a = imread(sprintf("office_%d.jpg", i));  
 4 |     subplot(3, 2, i); 
 5 |     imshow(a);  
 6 | end
 7 | 
 8 | for i = 1:6
 9 |     a = imread(sprintf("office_%d.jpg", i));  
10 |     subplot(3, 2, i); 
11 |     imhist(a);  
12 | end
13 | sgtitle('Histograms of the images ');


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/DIP/program9.m:
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 1 | 
 2 | for i = 1:6
 3 |     a = imread(sprintf("office_%d.jpg", i));  
 4 |     
 5 | 
 6 |     subplot(6, 2, 2*i-1);  
 7 |     imhist(a);  
 8 |     
 9 |     b = histeq(a);
10 |     subplot(6, 2, 2*i);  
11 |     imhist(b);  
12 |     
13 | end
14 | 
15 | sgtitle("Histogram and Equalized histogram")


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/ML lab/mydata/Find_s_data.csv:
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1 | sky,airtemperature,humidity,wind,water,forecast,play
2 | sunny,warm,normal,strong,warm,same,yes
3 | sunny,warm,high,strong,warm,same,yes
4 | rainy,cold,high,strong,warm,change,no
5 | sunny,warm,high,strong,cool,change,yes
6 | 


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/ML lab/mydata/candidate_data.csv:
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1 | sky,airtemperature,humidity,wind,water,forecast,play
2 | sunny,warm,normal,strong,warm,same,yes
3 | sunny,warm,high,strong,warm,same,yes
4 | rainy,cold,high,strong,warm,change,no
5 | sunny,warm,high,strong,cool,change,yes
6 | 


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/ML lab/mydata/data.csv:
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1 | time,weather,temprature,company,humidity,wind,enjoysports
2 | morning,sunny,warm,yes,mild,strong,yes
3 | evening,rainy,cold,no,mild,normal,no
4 | morning,sunny,moderate,yes,normal,normal,yes
5 | evening,sunny,cold,yes,high,strong,yes
6 | 


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/ML lab/mydata/tennis.csv:
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 1 | Outlook,Temperature,Humidity,Wind,Answer
 2 | sunny,hot,high,weak,no
 3 | sunny,hot,high,strong,no
 4 | overcast,hot,high,weak,yes
 5 | rain,mild,high,weak,yes
 6 | rain,cool,normal,weak,yes
 7 | rain,cool,normal,strong,no
 8 | overcast,cool,normal,strong,yes
 9 | sunny,mild,high,weak,no
10 | sunny,cool,normal,weak,yes
11 | rain,mild,normal,weak,yes
12 | sunny,mild,normal,strong,yes
13 | overcast,mild,high,strong,yes
14 | overcast,hot,normal,weak,yes
15 | rain,mild,high,strong,no
16 | 


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/ML lab/program1(introduction)/ml lab.pdf:
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https://raw.githubusercontent.com/Niraj-Ramnani/Lab-Record-6th-sem/333ed742d31d32b8c3e384d6dd4875e6c204ee81/ML lab/program1(introduction)/ml lab.pdf


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/ML lab/program10.ipynb:
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  1 | {
  2 |   "nbformat": 4,
  3 |   "nbformat_minor": 0,
  4 |   "metadata": {
  5 |     "colab": {
  6 |       "provenance": [],
  7 |       "authorship_tag": "ABX9TyP989ScWKxshchdmHcVizea",
  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 |         "<a href=\"https://colab.research.google.com/github/Niraj-Ramnani/Lab-Record-6th-sem/blob/main/ML%20lab/program10.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
 27 |       ]
 28 |     },
 29 |     {
 30 |       "cell_type": "code",
 31 |       "execution_count": null,
 32 |       "metadata": {
 33 |         "id": "_BhiivTE_vnH"
 34 |       },
 35 |       "outputs": [],
 36 |       "source": [
 37 |         "import numpy as np"
 38 |       ]
 39 |     },
 40 |     {
 41 |       "cell_type": "code",
 42 |       "source": [
 43 |         "x = np.array(([2,9],[1,5],[3,6]),dtype=float)\n",
 44 |         "y = np.array(([92],[86],[89]),dtype=float)\n",
 45 |         "x = x/np.amax(x,axis=0)\n",
 46 |         "y = y/100"
 47 |       ],
 48 |       "metadata": {
 49 |         "id": "W2wLPqAg_yQJ"
 50 |       },
 51 |       "execution_count": null,
 52 |       "outputs": []
 53 |     },
 54 |     {
 55 |       "cell_type": "code",
 56 |       "source": [
 57 |         "x"
 58 |       ],
 59 |       "metadata": {
 60 |         "colab": {
 61 |           "base_uri": "https://localhost:8080/"
 62 |         },
 63 |         "id": "SoPiIwI4ChND",
 64 |         "outputId": "3c58b2ee-059a-483d-89a8-ad5855306c78"
 65 |       },
 66 |       "execution_count": null,
 67 |       "outputs": [
 68 |         {
 69 |           "output_type": "execute_result",
 70 |           "data": {
 71 |             "text/plain": [
 72 |               "array([[0.66666667, 1.        ],\n",
 73 |               "       [0.33333333, 0.55555556],\n",
 74 |               "       [1.        , 0.66666667]])"
 75 |             ]
 76 |           },
 77 |           "metadata": {},
 78 |           "execution_count": 5
 79 |         }
 80 |       ]
 81 |     },
 82 |     {
 83 |       "cell_type": "code",
 84 |       "source": [
 85 |         "y"
 86 |       ],
 87 |       "metadata": {
 88 |         "colab": {
 89 |           "base_uri": "https://localhost:8080/"
 90 |         },
 91 |         "id": "LF6cwuYmCsNc",
 92 |         "outputId": "1786aff8-b854-4836-fa4f-64321fc9c840"
 93 |       },
 94 |       "execution_count": null,
 95 |       "outputs": [
 96 |         {
 97 |           "output_type": "execute_result",
 98 |           "data": {
 99 |             "text/plain": [
100 |               "array([[0.92],\n",
101 |               "       [0.86],\n",
102 |               "       [0.89]])"
103 |             ]
104 |           },
105 |           "metadata": {},
106 |           "execution_count": 6
107 |         }
108 |       ]
109 |     },
110 |     {
111 |       "cell_type": "code",
112 |       "source": [
113 |         "def sigmoid(x):\n",
114 |         "  return 1/(1 + np.exp(-x))\n",
115 |         "def sigmoid_grad(x):\n",
116 |         "  return x * (1-x)"
117 |       ],
118 |       "metadata": {
119 |         "id": "XxxGEQMY_425"
120 |       },
121 |       "execution_count": null,
122 |       "outputs": []
123 |     },
124 |     {
125 |       "cell_type": "code",
126 |       "source": [
127 |         "epoch = 1000\n",
128 |         "eta = 0.2\n",
129 |         "input_neurons = 2\n",
130 |         "hidden_neurons = 3\n",
131 |         "output_neurons = 1\n"
132 |       ],
133 |       "metadata": {
134 |         "id": "jhFgja0DAeuZ"
135 |       },
136 |       "execution_count": null,
137 |       "outputs": []
138 |     },
139 |     {
140 |       "cell_type": "code",
141 |       "source": [
142 |         "wh = np.random.uniform(size=(input_neurons,hidden_neurons))\n",
143 |         "bh = np.random.uniform(size=(1,hidden_neurons))\n",
144 |         "wout=np.random.uniform(size=(hidden_neurons,output_neurons))\n",
145 |         "bout=np.random.uniform(size=(1,output_neurons))\n"
146 |       ],
147 |       "metadata": {
148 |         "id": "D_BddzmVA4dl"
149 |       },
150 |       "execution_count": null,
151 |       "outputs": []
152 |     },
153 |     {
154 |       "cell_type": "code",
155 |       "source": [
156 |         "for i in range(epoch):\n",
157 |         "  h_ip = np.dot(x,wh) + bh\n",
158 |         "  h_act = sigmoid(h_ip)\n",
159 |         "  o_ip = np.dot(h_act,wout) + bout\n",
160 |         "  output = sigmoid(o_ip)\n",
161 |         "  Eo = y -output\n",
162 |         "  outgrad = sigmoid_grad(output)\n",
163 |         "  d_output = Eo * outgrad\n",
164 |         "  Eh = d_output.dot(wout.T)\n",
165 |         "  hiddengrad = sigmoid_grad(h_act)\n",
166 |         "  d_hidden = Eh * hiddengrad\n",
167 |         "  wout += h_act.T.dot(d_output) * eta\n",
168 |         "  wh += x.T.dot(d_hidden) * eta\n"
169 |       ],
170 |       "metadata": {
171 |         "id": "jxeeNlgzDP4e"
172 |       },
173 |       "execution_count": null,
174 |       "outputs": []
175 |     },
176 |     {
177 |       "cell_type": "code",
178 |       "source": [
179 |         "print(\"Normalized Input:\\n\",str(x))\n",
180 |         "print(\"Actual Output:\\n\",str(y))\n",
181 |         "print(\"Predicted Output:\\n\",output)"
182 |       ],
183 |       "metadata": {
184 |         "colab": {
185 |           "base_uri": "https://localhost:8080/"
186 |         },
187 |         "id": "gIZcUSKIDria",
188 |         "outputId": "9ed7312e-e0cf-452d-eedb-6f0975325809"
189 |       },
190 |       "execution_count": null,
191 |       "outputs": [
192 |         {
193 |           "output_type": "stream",
194 |           "name": "stdout",
195 |           "text": [
196 |             "Normalized Input:\n",
197 |             " [[0.66666667 1.        ]\n",
198 |             " [0.33333333 0.55555556]\n",
199 |             " [1.         0.66666667]]\n",
200 |             "Actual Output:\n",
201 |             " [[0.92]\n",
202 |             " [0.86]\n",
203 |             " [0.89]]\n",
204 |             "Predicted Output:\n",
205 |             " [[0.89631814]\n",
206 |             " [0.88019629]\n",
207 |             " [0.8932312 ]]\n"
208 |           ]
209 |         }
210 |       ]
211 |     },
212 |     {
213 |       "cell_type": "code",
214 |       "source": [],
215 |       "metadata": {
216 |         "id": "GXL6Z1gJD1OP"
217 |       },
218 |       "execution_count": null,
219 |       "outputs": []
220 |     }
221 |   ]
222 | }


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/ML lab/program2.ipynb:
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  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "# Run This if you are you using google collab"
  8 |    ]
  9 |   },
 10 |   {
 11 |    "cell_type": "code",
 12 |    "execution_count": null,
 13 |    "metadata": {},
 14 |    "outputs": [],
 15 |    "source": [
 16 |     "from google.colab import drive"
 17 |    ]
 18 |   },
 19 |   {
 20 |    "cell_type": "code",
 21 |    "execution_count": null,
 22 |    "metadata": {},
 23 |    "outputs": [],
 24 |    "source": [
 25 |     "%cd /content/drive/MyDrive/"
 26 |    ]
 27 |   },
 28 |   {
 29 |    "cell_type": "code",
 30 |    "execution_count": null,
 31 |    "metadata": {},
 32 |    "outputs": [],
 33 |    "source": [
 34 |     "drive.mount('/content/drive')"
 35 |    ]
 36 |   },
 37 |   {
 38 |    "cell_type": "code",
 39 |    "execution_count": 16,
 40 |    "metadata": {},
 41 |    "outputs": [],
 42 |    "source": [
 43 |     "!mkdir mydata"
 44 |    ]
 45 |   },
 46 |   {
 47 |    "cell_type": "code",
 48 |    "execution_count": null,
 49 |    "metadata": {},
 50 |    "outputs": [],
 51 |    "source": [
 52 |     "%cd mydata"
 53 |    ]
 54 |   },
 55 |   {
 56 |    "cell_type": "markdown",
 57 |    "metadata": {},
 58 |    "source": [
 59 |     "## Program 1"
 60 |    ]
 61 |   },
 62 |   {
 63 |    "cell_type": "markdown",
 64 |    "metadata": {},
 65 |    "source": [
 66 |     "*pip install numpy pandas matplotlib seaborn scikit-learn * use this on terminal"
 67 |    ]
 68 |   },
 69 |   {
 70 |    "cell_type": "markdown",
 71 |    "metadata": {},
 72 |    "source": [
 73 |     "# AIM : Write a program to create a data set with 5 entries using python in .csv format"
 74 |    ]
 75 |   },
 76 |   {
 77 |    "cell_type": "code",
 78 |    "execution_count": 7,
 79 |    "metadata": {},
 80 |    "outputs": [],
 81 |    "source": [
 82 |     "import pandas as pd \n",
 83 |     "import numpy as np"
 84 |    ]
 85 |   },
 86 |   {
 87 |    "cell_type": "code",
 88 |    "execution_count": 8,
 89 |    "metadata": {},
 90 |    "outputs": [],
 91 |    "source": [
 92 |     "import csv"
 93 |    ]
 94 |   },
 95 |   {
 96 |    "cell_type": "code",
 97 |    "execution_count": 9,
 98 |    "metadata": {},
 99 |    "outputs": [],
100 |    "source": [
101 |     "fields = ['time','weather','temprature','company','humidity','wind','enjoysports']"
102 |    ]
103 |   },
104 |   {
105 |    "cell_type": "code",
106 |    "execution_count": 10,
107 |    "metadata": {},
108 |    "outputs": [],
109 |    "source": [
110 |     "rows = [\n",
111 |     "    ['morning','sunny','warm','yes','mild','strong','yes'],\n",
112 |     "    ['evening','rainy','cold','no','mild','normal','no'],\n",
113 |     "    ['morning','sunny','moderate','yes','normal','normal','yes'],\n",
114 |     "    ['evening','sunny','cold','yes','high','strong','yes']\n",
115 |     "    ]"
116 |    ]
117 |   },
118 |   {
119 |    "cell_type": "code",
120 |    "execution_count": 11,
121 |    "metadata": {},
122 |    "outputs": [],
123 |    "source": [
124 |     "filename = \"data.csv\""
125 |    ]
126 |   },
127 |   {
128 |    "cell_type": "code",
129 |    "execution_count": 12,
130 |    "metadata": {},
131 |    "outputs": [],
132 |    "source": [
133 |     "with open('data.csv','w', newline='') as file:\n",
134 |     "  csvwriter = csv.writer(file)\n",
135 |     "  csvwriter.writerow(fields)\n",
136 |     "  csvwriter.writerows(rows)"
137 |    ]
138 |   },
139 |   {
140 |    "cell_type": "code",
141 |    "execution_count": 13,
142 |    "metadata": {},
143 |    "outputs": [
144 |     {
145 |      "name": "stdout",
146 |      "output_type": "stream",
147 |      "text": [
148 |       "      time weather temprature company humidity    wind enjoysports\n",
149 |       "0  morning   sunny       warm     yes     mild  strong         yes\n",
150 |       "1  evening   rainy       cold      no     mild  normal          no\n",
151 |       "2  morning   sunny   moderate     yes   normal  normal         yes\n",
152 |       "3  evening   sunny       cold     yes     high  strong         yes\n"
153 |      ]
154 |     }
155 |    ],
156 |    "source": [
157 |     "data = pd.read_csv('data.csv')\n",
158 |     "print(data)"
159 |    ]
160 |   },
161 |   {
162 |    "cell_type": "code",
163 |    "execution_count": 14,
164 |    "metadata": {},
165 |    "outputs": [
166 |     {
167 |      "name": "stdout",
168 |      "output_type": "stream",
169 |      "text": [
170 |       "[['morning' 'sunny' 'warm' 'yes' 'mild' 'strong']\n",
171 |       " ['evening' 'rainy' 'cold' 'no' 'mild' 'normal']\n",
172 |       " ['morning' 'sunny' 'moderate' 'yes' 'normal' 'normal']\n",
173 |       " ['evening' 'sunny' 'cold' 'yes' 'high' 'strong']]\n"
174 |      ]
175 |     }
176 |    ],
177 |    "source": [
178 |     "concepts = np.array(data.iloc[:,0:-1])\n",
179 |     "print(concepts)"
180 |    ]
181 |   },
182 |   {
183 |    "cell_type": "code",
184 |    "execution_count": 15,
185 |    "metadata": {},
186 |    "outputs": [
187 |     {
188 |      "name": "stdout",
189 |      "output_type": "stream",
190 |      "text": [
191 |       "['yes' 'no' 'yes' 'yes']\n"
192 |      ]
193 |     }
194 |    ],
195 |    "source": [
196 |     "target = np.array(data.iloc[:,-1])\n",
197 |     "print(target)"
198 |    ]
199 |   },
200 |   {
201 |    "cell_type": "code",
202 |    "execution_count": null,
203 |    "metadata": {},
204 |    "outputs": [],
205 |    "source": []
206 |   }
207 |  ],
208 |  "metadata": {
209 |   "kernelspec": {
210 |    "display_name": "Python 3",
211 |    "language": "python",
212 |    "name": "python3"
213 |   },
214 |   "language_info": {
215 |    "codemirror_mode": {
216 |     "name": "ipython",
217 |     "version": 3
218 |    },
219 |    "file_extension": ".py",
220 |    "mimetype": "text/x-python",
221 |    "name": "python",
222 |    "nbconvert_exporter": "python",
223 |    "pygments_lexer": "ipython3",
224 |    "version": "3.12.4"
225 |   }
226 |  },
227 |  "nbformat": 4,
228 |  "nbformat_minor": 2
229 | }
230 | 


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/ML lab/program3.ipynb:
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  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": null,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "%cd mydata/"
 10 |    ]
 11 |   },
 12 |   {
 13 |    "cell_type": "markdown",
 14 |    "metadata": {},
 15 |    "source": [
 16 |     "## Program 3 (FIND_S)\n",
 17 |     "### Implement and demonstrate the FIND-Salgorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file."
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "code",
 22 |    "execution_count": 9,
 23 |    "metadata": {},
 24 |    "outputs": [],
 25 |    "source": [
 26 |     "import pandas as pd\n",
 27 |     "import numpy as np\n",
 28 |     "import csv"
 29 |    ]
 30 |   },
 31 |   {
 32 |    "cell_type": "code",
 33 |    "execution_count": 18,
 34 |    "metadata": {},
 35 |    "outputs": [],
 36 |    "source": [
 37 |     "data = pd.read_csv('Find_s_data.csv')"
 38 |    ]
 39 |   },
 40 |   {
 41 |    "cell_type": "code",
 42 |    "execution_count": 20,
 43 |    "metadata": {},
 44 |    "outputs": [
 45 |     {
 46 |      "name": "stdout",
 47 |      "output_type": "stream",
 48 |      "text": [
 49 |       "concepts value are \n",
 50 |       " [['sunny' 'warm' 'normal' 'strong' 'warm' 'same']\n",
 51 |       " ['sunny' 'warm' 'high' 'strong' 'warm' 'same']\n",
 52 |       " ['rainy' 'cold' 'high' 'strong' 'warm' 'change']\n",
 53 |       " ['sunny' 'warm' 'high' 'strong' 'cool' 'change']]\n"
 54 |      ]
 55 |     }
 56 |    ],
 57 |    "source": [
 58 |     "concepts = np.array(data.iloc[:,0:-1])\n",
 59 |     "print(\"concepts value are \\n\" ,concepts)"
 60 |    ]
 61 |   },
 62 |   {
 63 |    "cell_type": "code",
 64 |    "execution_count": 21,
 65 |    "metadata": {},
 66 |    "outputs": [
 67 |     {
 68 |      "name": "stdout",
 69 |      "output_type": "stream",
 70 |      "text": [
 71 |       "target values are \n",
 72 |       " ['yes' 'yes' 'no' 'yes']\n"
 73 |      ]
 74 |     }
 75 |    ],
 76 |    "source": [
 77 |     "target = np.array(data.iloc[:,-1])\n",
 78 |     "print(\"target values are \\n\" ,target)"
 79 |    ]
 80 |   },
 81 |   {
 82 |    "cell_type": "code",
 83 |    "execution_count": 22,
 84 |    "metadata": {},
 85 |    "outputs": [],
 86 |    "source": [
 87 |     "def train(con , tar):\n",
 88 |     "  for i , val in enumerate(tar):\n",
 89 |     "    if val.lower() == 'yes':\n",
 90 |     "      specific_h = con[i].copy()\n",
 91 |     "      break\n",
 92 |     "  for i , val in enumerate(con):\n",
 93 |     "    if tar[i].lower() == 'yes':\n",
 94 |     "      for x in range(len(specific_h)):\n",
 95 |     "        if val[x] != specific_h[x]:\n",
 96 |     "          specific_h[x] = '?'\n",
 97 |     "        else:\n",
 98 |     "          pass\n",
 99 |     "  return specific_h"
100 |    ]
101 |   },
102 |   {
103 |    "cell_type": "code",
104 |    "execution_count": 23,
105 |    "metadata": {},
106 |    "outputs": [
107 |     {
108 |      "name": "stdout",
109 |      "output_type": "stream",
110 |      "text": [
111 |       "The final Hypothesis :  ['sunny' 'warm' '?' 'strong' '?' '?']\n"
112 |      ]
113 |     }
114 |    ],
115 |    "source": [
116 |     "print(\"The final Hypothesis : \" , train(concepts,target))"
117 |    ]
118 |   }
119 |  ],
120 |  "metadata": {
121 |   "kernelspec": {
122 |    "display_name": "Python 3",
123 |    "language": "python",
124 |    "name": "python3"
125 |   },
126 |   "language_info": {
127 |    "codemirror_mode": {
128 |     "name": "ipython",
129 |     "version": 3
130 |    },
131 |    "file_extension": ".py",
132 |    "mimetype": "text/x-python",
133 |    "name": "python",
134 |    "nbconvert_exporter": "python",
135 |    "pygments_lexer": "ipython3",
136 |    "version": "3.12.4"
137 |   }
138 |  },
139 |  "nbformat": 4,
140 |  "nbformat_minor": 2
141 | }
142 | 


--------------------------------------------------------------------------------
/ML lab/program4.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": null,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "%cd mydata/"
 10 |    ]
 11 |   },
 12 |   {
 13 |    "cell_type": "markdown",
 14 |    "metadata": {},
 15 |    "source": [
 16 |     "## Program 4 (CANDIDATE)\n",
 17 |     "### For a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Elimination algorithmto output a description of the set of all hypotheses consistent with the training examples."
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "code",
 22 |    "execution_count": 1,
 23 |    "metadata": {},
 24 |    "outputs": [],
 25 |    "source": [
 26 |     "import pandas as pd\n",
 27 |     "import numpy as np\n",
 28 |     "import csv"
 29 |    ]
 30 |   },
 31 |   {
 32 |    "cell_type": "code",
 33 |    "execution_count": 4,
 34 |    "metadata": {},
 35 |    "outputs": [],
 36 |    "source": [
 37 |     "data = pd.read_csv('candidate_data.csv')"
 38 |    ]
 39 |   },
 40 |   {
 41 |    "cell_type": "code",
 42 |    "execution_count": 5,
 43 |    "metadata": {},
 44 |    "outputs": [
 45 |     {
 46 |      "name": "stdout",
 47 |      "output_type": "stream",
 48 |      "text": [
 49 |       "concepts value are \n",
 50 |       " [['sunny' 'warm' 'normal' 'strong' 'warm' 'same']\n",
 51 |       " ['sunny' 'warm' 'high' 'strong' 'warm' 'same']\n",
 52 |       " ['rainy' 'cold' 'high' 'strong' 'warm' 'change']\n",
 53 |       " ['sunny' 'warm' 'high' 'strong' 'cool' 'change']]\n"
 54 |      ]
 55 |     }
 56 |    ],
 57 |    "source": [
 58 |     "concepts = np.array(data.iloc[:,0:-1])\n",
 59 |     "print(\"concepts value are \\n\" ,concepts)"
 60 |    ]
 61 |   },
 62 |   {
 63 |    "cell_type": "code",
 64 |    "execution_count": 6,
 65 |    "metadata": {},
 66 |    "outputs": [
 67 |     {
 68 |      "name": "stdout",
 69 |      "output_type": "stream",
 70 |      "text": [
 71 |       "target values are \n",
 72 |       " ['yes' 'yes' 'no' 'yes']\n"
 73 |      ]
 74 |     }
 75 |    ],
 76 |    "source": [
 77 |     "target = np.array(data.iloc[:,-1])\n",
 78 |     "print(\"target values are \\n\" ,target)"
 79 |    ]
 80 |   },
 81 |   {
 82 |    "cell_type": "code",
 83 |    "execution_count": null,
 84 |    "metadata": {},
 85 |    "outputs": [],
 86 |    "source": [
 87 |     "def learn(concepts, target):\n",
 88 |     "    specific_h = concepts[0].copy()\n",
 89 |     "    print(\"initialization of specific_h and general_h\")\n",
 90 |     "    print(\"specific_h\", specific_h)\n",
 91 |     "\n",
 92 |     "    general_h = [[\"?\" for i in range(len(specific_h))] for i in range(len(specific_h))]\n",
 93 |     "    print(\"general_h\", general_h)\n",
 94 |     "\n",
 95 |     "    for i, h in enumerate(concepts):\n",
 96 |     "        if target[i] == \"yes\":\n",
 97 |     "            for x in range(len(specific_h)):\n",
 98 |     "                if h[x] != specific_h[x]:\n",
 99 |     "                    specific_h[x] = '?'\n",
100 |     "                    general_h[x][x] = '?'\n",
101 |     "\n",
102 |     "        if target[i] == \"no\":\n",
103 |     "            for x in range(len(specific_h)):\n",
104 |     "                if h[x] != specific_h[x]:\n",
105 |     "                    general_h[x][x] = specific_h[x]\n",
106 |     "                else:\n",
107 |     "                    general_h[x][x] = '?'\n",
108 |     "\n",
109 |     "        print(\"steps of candidate elimination algorithm\", i + 1)\n",
110 |     "        print(specific_h)\n",
111 |     "        print(general_h)\n",
112 |     "\n",
113 |     "    indices = [i for i, val in enumerate(general_h) if val == ['?', '?', '?', '?', '?', '?']]\n",
114 |     "    for i in indices:\n",
115 |     "        general_h.remove(['?', '?', '?', '?', '?', '?'])\n",
116 |     "\n",
117 |     "    return specific_h, general_h\n",
118 |     "\n",
119 |     "\n",
120 |     "s_final, g_final = learn(concepts, target)\n",
121 |     "print(\"Final Specific_h:\", s_final, sep=\"\\n\")\n",
122 |     "print(\"Final General_h:\", g_final, sep=\"\\n\")\n"
123 |    ]
124 |   },
125 |   {
126 |    "cell_type": "code",
127 |    "execution_count": 10,
128 |    "metadata": {},
129 |    "outputs": [
130 |     {
131 |      "name": "stdout",
132 |      "output_type": "stream",
133 |      "text": [
134 |       "\n",
135 |       "Final Specific Hypothesis: ['sunny' 'warm' '?' 'strong' '?' '?']\n",
136 |       "Final General Hypothesis: [['sunny', '?', '?', '?', '?', '?'], ['?', 'warm', '?', '?', '?', '?']]\n"
137 |      ]
138 |     }
139 |    ],
140 |    "source": [
141 |     "print(\"\\nFinal Specific Hypothesis:\", s_final)\n",
142 |     "print(\"Final General Hypothesis:\", g_final)"
143 |    ]
144 |   }
145 |  ],
146 |  "metadata": {
147 |   "kernelspec": {
148 |    "display_name": "Python 3",
149 |    "language": "python",
150 |    "name": "python3"
151 |   },
152 |   "language_info": {
153 |    "codemirror_mode": {
154 |     "name": "ipython",
155 |     "version": 3
156 |    },
157 |    "file_extension": ".py",
158 |    "mimetype": "text/x-python",
159 |    "name": "python",
160 |    "nbconvert_exporter": "python",
161 |    "pygments_lexer": "ipython3",
162 |    "version": "3.12.4"
163 |   }
164 |  },
165 |  "nbformat": 4,
166 |  "nbformat_minor": 2
167 | }
168 | 


--------------------------------------------------------------------------------
/ML lab/program5.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": null,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "%cd mydata/"
 10 |    ]
 11 |   },
 12 |   {
 13 |    "cell_type": "markdown",
 14 |    "metadata": {},
 15 |    "source": [
 16 |     "## Program 5 (NAIVE_BAYESIAN)\n",
 17 |     "### Write a program to implement the naïve Bayesian classifier for a sample training data set stored as a .CSV file. Compute the accuracy of the classifier, considering few test data sets."
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "code",
 22 |    "execution_count": 2,
 23 |    "metadata": {},
 24 |    "outputs": [],
 25 |    "source": [
 26 |     "import pandas as pd\n",
 27 |     "from sklearn import tree\n",
 28 |     "from sklearn.preprocessing import LabelEncoder\n",
 29 |     "from sklearn.naive_bayes import GaussianNB"
 30 |    ]
 31 |   },
 32 |   {
 33 |    "cell_type": "code",
 34 |    "execution_count": 3,
 35 |    "metadata": {},
 36 |    "outputs": [
 37 |     {
 38 |      "name": "stdout",
 39 |      "output_type": "stream",
 40 |      "text": [
 41 |       "the first 5 value of data is : \n",
 42 |       "     Outlook Temperature Humidity    Wind Answer\n",
 43 |       "0     sunny         hot     high    weak     no\n",
 44 |       "1     sunny         hot     high  strong     no\n",
 45 |       "2  overcast         hot     high    weak    yes\n",
 46 |       "3      rain        mild     high    weak    yes\n",
 47 |       "4      rain        cool   normal    weak    yes\n"
 48 |      ]
 49 |     }
 50 |    ],
 51 |    "source": [
 52 |     "data = pd.read_csv('tennis.csv')\n",
 53 |     "print(\"the first 5 value of data is : \\n\" , data.head())"
 54 |    ]
 55 |   },
 56 |   {
 57 |    "cell_type": "code",
 58 |    "execution_count": 4,
 59 |    "metadata": {},
 60 |    "outputs": [
 61 |     {
 62 |      "name": "stdout",
 63 |      "output_type": "stream",
 64 |      "text": [
 65 |       "\n",
 66 |       "The first 5 value of train data is \n",
 67 |       "     Outlook Temperature Humidity    Wind\n",
 68 |       "0     sunny         hot     high    weak\n",
 69 |       "1     sunny         hot     high  strong\n",
 70 |       "2  overcast         hot     high    weak\n",
 71 |       "3      rain        mild     high    weak\n",
 72 |       "4      rain        cool   normal    weak\n"
 73 |      ]
 74 |     }
 75 |    ],
 76 |    "source": [
 77 |     "x = data.iloc[:,:-1]\n",
 78 |     "print(\"\\nThe first 5 value of train data is \\n\",x.head())"
 79 |    ]
 80 |   },
 81 |   {
 82 |    "cell_type": "code",
 83 |    "execution_count": 5,
 84 |    "metadata": {},
 85 |    "outputs": [
 86 |     {
 87 |      "name": "stdout",
 88 |      "output_type": "stream",
 89 |      "text": [
 90 |       "\n",
 91 |       "The first 5 value of train output is \n",
 92 |       " 0     no\n",
 93 |       "1     no\n",
 94 |       "2    yes\n",
 95 |       "3    yes\n",
 96 |       "4    yes\n",
 97 |       "Name: Answer, dtype: object\n"
 98 |      ]
 99 |     }
100 |    ],
101 |    "source": [
102 |     "y = data.iloc[:, -1]\n",
103 |     "print(\"\\nThe first 5 value of train output is \\n\",y.head())"
104 |    ]
105 |   },
106 |   {
107 |    "cell_type": "code",
108 |    "execution_count": null,
109 |    "metadata": {},
110 |    "outputs": [],
111 |    "source": [
112 |     "le_Outlook = LabelEncoder()\n",
113 |     "x.Outlook = le_Outlook.fit_transform(x.Outlook)\n",
114 |     "le_Temperature = LabelEncoder()\n",
115 |     "x.Temperature = le_Temperature.fit_transform(x.Temperature)\n",
116 |     "le_Humidity = LabelEncoder()\n",
117 |     "x.Humidity = le_Humidity.fit_transform(x.Humidity)\n",
118 |     "le_Wind = LabelEncoder()\n",
119 |     "x.Wind = le_Wind.fit_transform(x.Wind)"
120 |    ]
121 |   },
122 |   {
123 |    "cell_type": "code",
124 |    "execution_count": 14,
125 |    "metadata": {},
126 |    "outputs": [
127 |     {
128 |      "name": "stdout",
129 |      "output_type": "stream",
130 |      "text": [
131 |       "\n",
132 |       " Now the train data is : \n",
133 |       "    Outlook  Temperature  Humidity  Wind\n",
134 |       "0        2            1         0     1\n",
135 |       "1        2            1         0     0\n",
136 |       "2        0            1         0     1\n",
137 |       "3        1            2         0     1\n",
138 |       "4        1            0         1     1\n",
139 |       "\n",
140 |       " Now the train output is : \n",
141 |       " [0 0 1 1 1 0 1 0 1 1 1 1 1 0]\n"
142 |      ]
143 |     }
144 |    ],
145 |    "source": [
146 |     "print(\"\\n Now the train data is : \\n\",x.head())\n",
147 |     "le_play = LabelEncoder()\n",
148 |     "y = le_play.fit_transform(y)\n",
149 |     "print(\"\\n Now the train output is : \\n\",y)"
150 |    ]
151 |   },
152 |   {
153 |    "cell_type": "code",
154 |    "execution_count": 15,
155 |    "metadata": {},
156 |    "outputs": [
157 |     {
158 |      "data": {
159 |       "text/html": [
160 |        "<style>#sk-container-id-2 {\n",
161 |        "  /* Definition of color scheme common for light and dark mode */\n",
162 |        "  --sklearn-color-text: #000;\n",
163 |        "  --sklearn-color-text-muted: #666;\n",
164 |        "  --sklearn-color-line: gray;\n",
165 |        "  /* Definition of color scheme for unfitted estimators */\n",
166 |        "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
167 |        "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
168 |        "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
169 |        "  --sklearn-color-unfitted-level-3: chocolate;\n",
170 |        "  /* Definition of color scheme for fitted estimators */\n",
171 |        "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
172 |        "  --sklearn-color-fitted-level-1: #d4ebff;\n",
173 |        "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
174 |        "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
175 |        "\n",
176 |        "  /* Specific color for light theme */\n",
177 |        "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
178 |        "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
179 |        "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
180 |        "  --sklearn-color-icon: #696969;\n",
181 |        "\n",
182 |        "  @media (prefers-color-scheme: dark) {\n",
183 |        "    /* Redefinition of color scheme for dark theme */\n",
184 |        "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
185 |        "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
186 |        "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
187 |        "    --sklearn-color-icon: #878787;\n",
188 |        "  }\n",
189 |        "}\n",
190 |        "\n",
191 |        "#sk-container-id-2 {\n",
192 |        "  color: var(--sklearn-color-text);\n",
193 |        "}\n",
194 |        "\n",
195 |        "#sk-container-id-2 pre {\n",
196 |        "  padding: 0;\n",
197 |        "}\n",
198 |        "\n",
199 |        "#sk-container-id-2 input.sk-hidden--visually {\n",
200 |        "  border: 0;\n",
201 |        "  clip: rect(1px 1px 1px 1px);\n",
202 |        "  clip: rect(1px, 1px, 1px, 1px);\n",
203 |        "  height: 1px;\n",
204 |        "  margin: -1px;\n",
205 |        "  overflow: hidden;\n",
206 |        "  padding: 0;\n",
207 |        "  position: absolute;\n",
208 |        "  width: 1px;\n",
209 |        "}\n",
210 |        "\n",
211 |        "#sk-container-id-2 div.sk-dashed-wrapped {\n",
212 |        "  border: 1px dashed var(--sklearn-color-line);\n",
213 |        "  margin: 0 0.4em 0.5em 0.4em;\n",
214 |        "  box-sizing: border-box;\n",
215 |        "  padding-bottom: 0.4em;\n",
216 |        "  background-color: var(--sklearn-color-background);\n",
217 |        "}\n",
218 |        "\n",
219 |        "#sk-container-id-2 div.sk-container {\n",
220 |        "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
221 |        "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
222 |        "     so we also need the `!important` here to be able to override the\n",
223 |        "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
224 |        "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
225 |        "  display: inline-block !important;\n",
226 |        "  position: relative;\n",
227 |        "}\n",
228 |        "\n",
229 |        "#sk-container-id-2 div.sk-text-repr-fallback {\n",
230 |        "  display: none;\n",
231 |        "}\n",
232 |        "\n",
233 |        "div.sk-parallel-item,\n",
234 |        "div.sk-serial,\n",
235 |        "div.sk-item {\n",
236 |        "  /* draw centered vertical line to link estimators */\n",
237 |        "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
238 |        "  background-size: 2px 100%;\n",
239 |        "  background-repeat: no-repeat;\n",
240 |        "  background-position: center center;\n",
241 |        "}\n",
242 |        "\n",
243 |        "/* Parallel-specific style estimator block */\n",
244 |        "\n",
245 |        "#sk-container-id-2 div.sk-parallel-item::after {\n",
246 |        "  content: \"\";\n",
247 |        "  width: 100%;\n",
248 |        "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
249 |        "  flex-grow: 1;\n",
250 |        "}\n",
251 |        "\n",
252 |        "#sk-container-id-2 div.sk-parallel {\n",
253 |        "  display: flex;\n",
254 |        "  align-items: stretch;\n",
255 |        "  justify-content: center;\n",
256 |        "  background-color: var(--sklearn-color-background);\n",
257 |        "  position: relative;\n",
258 |        "}\n",
259 |        "\n",
260 |        "#sk-container-id-2 div.sk-parallel-item {\n",
261 |        "  display: flex;\n",
262 |        "  flex-direction: column;\n",
263 |        "}\n",
264 |        "\n",
265 |        "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
266 |        "  align-self: flex-end;\n",
267 |        "  width: 50%;\n",
268 |        "}\n",
269 |        "\n",
270 |        "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
271 |        "  align-self: flex-start;\n",
272 |        "  width: 50%;\n",
273 |        "}\n",
274 |        "\n",
275 |        "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
276 |        "  width: 0;\n",
277 |        "}\n",
278 |        "\n",
279 |        "/* Serial-specific style estimator block */\n",
280 |        "\n",
281 |        "#sk-container-id-2 div.sk-serial {\n",
282 |        "  display: flex;\n",
283 |        "  flex-direction: column;\n",
284 |        "  align-items: center;\n",
285 |        "  background-color: var(--sklearn-color-background);\n",
286 |        "  padding-right: 1em;\n",
287 |        "  padding-left: 1em;\n",
288 |        "}\n",
289 |        "\n",
290 |        "\n",
291 |        "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
292 |        "clickable and can be expanded/collapsed.\n",
293 |        "- Pipeline and ColumnTransformer use this feature and define the default style\n",
294 |        "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
295 |        "*/\n",
296 |        "\n",
297 |        "/* Pipeline and ColumnTransformer style (default) */\n",
298 |        "\n",
299 |        "#sk-container-id-2 div.sk-toggleable {\n",
300 |        "  /* Default theme specific background. It is overwritten whether we have a\n",
301 |        "  specific estimator or a Pipeline/ColumnTransformer */\n",
302 |        "  background-color: var(--sklearn-color-background);\n",
303 |        "}\n",
304 |        "\n",
305 |        "/* Toggleable label */\n",
306 |        "#sk-container-id-2 label.sk-toggleable__label {\n",
307 |        "  cursor: pointer;\n",
308 |        "  display: flex;\n",
309 |        "  width: 100%;\n",
310 |        "  margin-bottom: 0;\n",
311 |        "  padding: 0.5em;\n",
312 |        "  box-sizing: border-box;\n",
313 |        "  text-align: center;\n",
314 |        "  align-items: start;\n",
315 |        "  justify-content: space-between;\n",
316 |        "  gap: 0.5em;\n",
317 |        "}\n",
318 |        "\n",
319 |        "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
320 |        "  font-size: 0.6rem;\n",
321 |        "  font-weight: lighter;\n",
322 |        "  color: var(--sklearn-color-text-muted);\n",
323 |        "}\n",
324 |        "\n",
325 |        "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
326 |        "  /* Arrow on the left of the label */\n",
327 |        "  content: \"▸\";\n",
328 |        "  float: left;\n",
329 |        "  margin-right: 0.25em;\n",
330 |        "  color: var(--sklearn-color-icon);\n",
331 |        "}\n",
332 |        "\n",
333 |        "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
334 |        "  color: var(--sklearn-color-text);\n",
335 |        "}\n",
336 |        "\n",
337 |        "/* Toggleable content - dropdown */\n",
338 |        "\n",
339 |        "#sk-container-id-2 div.sk-toggleable__content {\n",
340 |        "  max-height: 0;\n",
341 |        "  max-width: 0;\n",
342 |        "  overflow: hidden;\n",
343 |        "  text-align: left;\n",
344 |        "  /* unfitted */\n",
345 |        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
346 |        "}\n",
347 |        "\n",
348 |        "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
349 |        "  /* fitted */\n",
350 |        "  background-color: var(--sklearn-color-fitted-level-0);\n",
351 |        "}\n",
352 |        "\n",
353 |        "#sk-container-id-2 div.sk-toggleable__content pre {\n",
354 |        "  margin: 0.2em;\n",
355 |        "  border-radius: 0.25em;\n",
356 |        "  color: var(--sklearn-color-text);\n",
357 |        "  /* unfitted */\n",
358 |        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
359 |        "}\n",
360 |        "\n",
361 |        "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
362 |        "  /* unfitted */\n",
363 |        "  background-color: var(--sklearn-color-fitted-level-0);\n",
364 |        "}\n",
365 |        "\n",
366 |        "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
367 |        "  /* Expand drop-down */\n",
368 |        "  max-height: 200px;\n",
369 |        "  max-width: 100%;\n",
370 |        "  overflow: auto;\n",
371 |        "}\n",
372 |        "\n",
373 |        "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
374 |        "  content: \"▾\";\n",
375 |        "}\n",
376 |        "\n",
377 |        "/* Pipeline/ColumnTransformer-specific style */\n",
378 |        "\n",
379 |        "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
380 |        "  color: var(--sklearn-color-text);\n",
381 |        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
382 |        "}\n",
383 |        "\n",
384 |        "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
385 |        "  background-color: var(--sklearn-color-fitted-level-2);\n",
386 |        "}\n",
387 |        "\n",
388 |        "/* Estimator-specific style */\n",
389 |        "\n",
390 |        "/* Colorize estimator box */\n",
391 |        "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
392 |        "  /* unfitted */\n",
393 |        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
394 |        "}\n",
395 |        "\n",
396 |        "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
397 |        "  /* fitted */\n",
398 |        "  background-color: var(--sklearn-color-fitted-level-2);\n",
399 |        "}\n",
400 |        "\n",
401 |        "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
402 |        "#sk-container-id-2 div.sk-label label {\n",
403 |        "  /* The background is the default theme color */\n",
404 |        "  color: var(--sklearn-color-text-on-default-background);\n",
405 |        "}\n",
406 |        "\n",
407 |        "/* On hover, darken the color of the background */\n",
408 |        "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
409 |        "  color: var(--sklearn-color-text);\n",
410 |        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
411 |        "}\n",
412 |        "\n",
413 |        "/* Label box, darken color on hover, fitted */\n",
414 |        "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
415 |        "  color: var(--sklearn-color-text);\n",
416 |        "  background-color: var(--sklearn-color-fitted-level-2);\n",
417 |        "}\n",
418 |        "\n",
419 |        "/* Estimator label */\n",
420 |        "\n",
421 |        "#sk-container-id-2 div.sk-label label {\n",
422 |        "  font-family: monospace;\n",
423 |        "  font-weight: bold;\n",
424 |        "  display: inline-block;\n",
425 |        "  line-height: 1.2em;\n",
426 |        "}\n",
427 |        "\n",
428 |        "#sk-container-id-2 div.sk-label-container {\n",
429 |        "  text-align: center;\n",
430 |        "}\n",
431 |        "\n",
432 |        "/* Estimator-specific */\n",
433 |        "#sk-container-id-2 div.sk-estimator {\n",
434 |        "  font-family: monospace;\n",
435 |        "  border: 1px dotted var(--sklearn-color-border-box);\n",
436 |        "  border-radius: 0.25em;\n",
437 |        "  box-sizing: border-box;\n",
438 |        "  margin-bottom: 0.5em;\n",
439 |        "  /* unfitted */\n",
440 |        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
441 |        "}\n",
442 |        "\n",
443 |        "#sk-container-id-2 div.sk-estimator.fitted {\n",
444 |        "  /* fitted */\n",
445 |        "  background-color: var(--sklearn-color-fitted-level-0);\n",
446 |        "}\n",
447 |        "\n",
448 |        "/* on hover */\n",
449 |        "#sk-container-id-2 div.sk-estimator:hover {\n",
450 |        "  /* unfitted */\n",
451 |        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
452 |        "}\n",
453 |        "\n",
454 |        "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
455 |        "  /* fitted */\n",
456 |        "  background-color: var(--sklearn-color-fitted-level-2);\n",
457 |        "}\n",
458 |        "\n",
459 |        "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
460 |        "\n",
461 |        "/* Common style for \"i\" and \"?\" */\n",
462 |        "\n",
463 |        ".sk-estimator-doc-link,\n",
464 |        "a:link.sk-estimator-doc-link,\n",
465 |        "a:visited.sk-estimator-doc-link {\n",
466 |        "  float: right;\n",
467 |        "  font-size: smaller;\n",
468 |        "  line-height: 1em;\n",
469 |        "  font-family: monospace;\n",
470 |        "  background-color: var(--sklearn-color-background);\n",
471 |        "  border-radius: 1em;\n",
472 |        "  height: 1em;\n",
473 |        "  width: 1em;\n",
474 |        "  text-decoration: none !important;\n",
475 |        "  margin-left: 0.5em;\n",
476 |        "  text-align: center;\n",
477 |        "  /* unfitted */\n",
478 |        "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
479 |        "  color: var(--sklearn-color-unfitted-level-1);\n",
480 |        "}\n",
481 |        "\n",
482 |        ".sk-estimator-doc-link.fitted,\n",
483 |        "a:link.sk-estimator-doc-link.fitted,\n",
484 |        "a:visited.sk-estimator-doc-link.fitted {\n",
485 |        "  /* fitted */\n",
486 |        "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
487 |        "  color: var(--sklearn-color-fitted-level-1);\n",
488 |        "}\n",
489 |        "\n",
490 |        "/* On hover */\n",
491 |        "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
492 |        ".sk-estimator-doc-link:hover,\n",
493 |        "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
494 |        ".sk-estimator-doc-link:hover {\n",
495 |        "  /* unfitted */\n",
496 |        "  background-color: var(--sklearn-color-unfitted-level-3);\n",
497 |        "  color: var(--sklearn-color-background);\n",
498 |        "  text-decoration: none;\n",
499 |        "}\n",
500 |        "\n",
501 |        "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
502 |        ".sk-estimator-doc-link.fitted:hover,\n",
503 |        "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
504 |        ".sk-estimator-doc-link.fitted:hover {\n",
505 |        "  /* fitted */\n",
506 |        "  background-color: var(--sklearn-color-fitted-level-3);\n",
507 |        "  color: var(--sklearn-color-background);\n",
508 |        "  text-decoration: none;\n",
509 |        "}\n",
510 |        "\n",
511 |        "/* Span, style for the box shown on hovering the info icon */\n",
512 |        ".sk-estimator-doc-link span {\n",
513 |        "  display: none;\n",
514 |        "  z-index: 9999;\n",
515 |        "  position: relative;\n",
516 |        "  font-weight: normal;\n",
517 |        "  right: .2ex;\n",
518 |        "  padding: .5ex;\n",
519 |        "  margin: .5ex;\n",
520 |        "  width: min-content;\n",
521 |        "  min-width: 20ex;\n",
522 |        "  max-width: 50ex;\n",
523 |        "  color: var(--sklearn-color-text);\n",
524 |        "  box-shadow: 2pt 2pt 4pt #999;\n",
525 |        "  /* unfitted */\n",
526 |        "  background: var(--sklearn-color-unfitted-level-0);\n",
527 |        "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
528 |        "}\n",
529 |        "\n",
530 |        ".sk-estimator-doc-link.fitted span {\n",
531 |        "  /* fitted */\n",
532 |        "  background: var(--sklearn-color-fitted-level-0);\n",
533 |        "  border: var(--sklearn-color-fitted-level-3);\n",
534 |        "}\n",
535 |        "\n",
536 |        ".sk-estimator-doc-link:hover span {\n",
537 |        "  display: block;\n",
538 |        "}\n",
539 |        "\n",
540 |        "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
541 |        "\n",
542 |        "#sk-container-id-2 a.estimator_doc_link {\n",
543 |        "  float: right;\n",
544 |        "  font-size: 1rem;\n",
545 |        "  line-height: 1em;\n",
546 |        "  font-family: monospace;\n",
547 |        "  background-color: var(--sklearn-color-background);\n",
548 |        "  border-radius: 1rem;\n",
549 |        "  height: 1rem;\n",
550 |        "  width: 1rem;\n",
551 |        "  text-decoration: none;\n",
552 |        "  /* unfitted */\n",
553 |        "  color: var(--sklearn-color-unfitted-level-1);\n",
554 |        "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
555 |        "}\n",
556 |        "\n",
557 |        "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
558 |        "  /* fitted */\n",
559 |        "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
560 |        "  color: var(--sklearn-color-fitted-level-1);\n",
561 |        "}\n",
562 |        "\n",
563 |        "/* On hover */\n",
564 |        "#sk-container-id-2 a.estimator_doc_link:hover {\n",
565 |        "  /* unfitted */\n",
566 |        "  background-color: var(--sklearn-color-unfitted-level-3);\n",
567 |        "  color: var(--sklearn-color-background);\n",
568 |        "  text-decoration: none;\n",
569 |        "}\n",
570 |        "\n",
571 |        "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
572 |        "  /* fitted */\n",
573 |        "  background-color: var(--sklearn-color-fitted-level-3);\n",
574 |        "}\n",
575 |        "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GaussianNB()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>GaussianNB</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.naive_bayes.GaussianNB.html\">?<span>Documentation for GaussianNB</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>GaussianNB()</pre></div> </div></div></div></div>"
576 |       ],
577 |       "text/plain": [
578 |        "GaussianNB()"
579 |       ]
580 |      },
581 |      "execution_count": 15,
582 |      "metadata": {},
583 |      "output_type": "execute_result"
584 |     }
585 |    ],
586 |    "source": [
587 |     "from sklearn.model_selection import train_test_split\n",
588 |     "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.20)\n",
589 |     "classifier = GaussianNB()\n",
590 |     "classifier.fit(x_train, y_train)"
591 |    ]
592 |   },
593 |   {
594 |    "cell_type": "code",
595 |    "execution_count": 16,
596 |    "metadata": {},
597 |    "outputs": [
598 |     {
599 |      "name": "stdout",
600 |      "output_type": "stream",
601 |      "text": [
602 |       "Accuracy is: 0.6666666666666666\n"
603 |      ]
604 |     }
605 |    ],
606 |    "source": [
607 |     "from sklearn.metrics import accuracy_score\n",
608 |     "print(\"Accuracy is:\", accuracy_score(classifier.predict(x_test), y_test))"
609 |    ]
610 |   },
611 |   {
612 |    "cell_type": "code",
613 |    "execution_count": null,
614 |    "metadata": {},
615 |    "outputs": [],
616 |    "source": []
617 |   }
618 |  ],
619 |  "metadata": {
620 |   "kernelspec": {
621 |    "display_name": "Python 3",
622 |    "language": "python",
623 |    "name": "python3"
624 |   },
625 |   "language_info": {
626 |    "codemirror_mode": {
627 |     "name": "ipython",
628 |     "version": 3
629 |    },
630 |    "file_extension": ".py",
631 |    "mimetype": "text/x-python",
632 |    "name": "python",
633 |    "nbconvert_exporter": "python",
634 |    "pygments_lexer": "ipython3",
635 |    "version": "3.12.4"
636 |   }
637 |  },
638 |  "nbformat": 4,
639 |  "nbformat_minor": 2
640 | }
641 | 


--------------------------------------------------------------------------------
/ML lab/program6.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |   "cells": [
  3 |     {
  4 |       "cell_type": "markdown",
  5 |       "metadata": {
  6 |         "colab_type": "text",
  7 |         "id": "view-in-github"
  8 |       },
  9 |       "source": [
 10 |         "<a href=\"https://colab.research.google.com/github/Niraj-Ramnani/Lab-Record-6th-sem/blob/main/ML%20lab/program6.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
 11 |       ]
 12 |     },
 13 |     {
 14 |       "cell_type": "markdown",
 15 |       "metadata": {},
 16 |       "source": [
 17 |         "### Assuming a set of documents that need to be classified, use the naïve Bayesian Classifier model to perform this task. Built-in Java classes/API can be used to write the program. Calculate the accuracy, precision, and recall for your data set."
 18 |       ]
 19 |     },
 20 |     {
 21 |       "cell_type": "code",
 22 |       "execution_count": null,
 23 |       "metadata": {
 24 |         "colab": {
 25 |           "base_uri": "https://localhost:8080/"
 26 |         },
 27 |         "id": "jLAz6hwLrk04",
 28 |         "outputId": "852dbb98-1468-4e60-d78f-103a4cc29c7e"
 29 |       },
 30 |       "outputs": [
 31 |         {
 32 |           "name": "stdout",
 33 |           "output_type": "stream",
 34 |           "text": [
 35 |             "The dimmension of the dataset  (18, 2)\n",
 36 |             "0                      I love this sandwich\n",
 37 |             "1                  This is an amazing place\n",
 38 |             "2        I feel very good about these beers\n",
 39 |             "3                      This is my best work\n",
 40 |             "4                      What an awesome view\n",
 41 |             "5             I do not like this restaurant\n",
 42 |             "6                  I am tired of this stuff\n",
 43 |             "7                    I can't deal with this\n",
 44 |             "8                      He is my sworn enemy\n",
 45 |             "9                       My boss is horrible\n",
 46 |             "10                 This is an awesome place\n",
 47 |             "11    I do not like the taste of this juice\n",
 48 |             "12                          I love to dance\n",
 49 |             "13        I am sick and tired of this place\n",
 50 |             "14                     What a great holiday\n",
 51 |             "15           That is a bad locality to stay\n",
 52 |             "16           We will have good fun tomorrow\n",
 53 |             "17         I went to my enemy's house today\n",
 54 |             "Name: message, dtype: object\n",
 55 |             "0     1\n",
 56 |             "1     1\n",
 57 |             "2     1\n",
 58 |             "3     1\n",
 59 |             "4     1\n",
 60 |             "5     0\n",
 61 |             "6     0\n",
 62 |             "7     0\n",
 63 |             "8     0\n",
 64 |             "9     0\n",
 65 |             "10    1\n",
 66 |             "11    0\n",
 67 |             "12    1\n",
 68 |             "13    0\n",
 69 |             "14    1\n",
 70 |             "15    0\n",
 71 |             "16    1\n",
 72 |             "17    0\n",
 73 |             "Name: labelnum, dtype: int64\n"
 74 |           ]
 75 |         }
 76 |       ],
 77 |       "source": [
 78 |         "import pandas as pd\n",
 79 |         "msg = pd.read_csv(\"naivetext.csv\", names = ['message','label'])\n",
 80 |         "print('The dimmension of the dataset ', msg.shape)\n",
 81 |         "msg['labelnum'] = msg.label.map({'pos':1, 'neg':0})\n",
 82 |         "X = msg.message\n",
 83 |         "y = msg.labelnum\n",
 84 |         "print(X)\n",
 85 |         "print(y)"
 86 |       ]
 87 |     },
 88 |     {
 89 |       "cell_type": "code",
 90 |       "execution_count": null,
 91 |       "metadata": {
 92 |         "colab": {
 93 |           "base_uri": "https://localhost:8080/"
 94 |         },
 95 |         "id": "pc4LmH0rvR-Q",
 96 |         "outputId": "8e80f21c-2478-4f46-a9e0-a97db5426676"
 97 |       },
 98 |       "outputs": [
 99 |         {
100 |           "name": "stdout",
101 |           "output_type": "stream",
102 |           "text": [
103 |             "\n",
104 |             " the total number of training data  (14,)\n",
105 |             "\n",
106 |             " the total number of testing data  (4,)\n"
107 |           ]
108 |         }
109 |       ],
110 |       "source": [
111 |         "# splitting the data set into train and test data set\n",
112 |         "from sklearn.model_selection import train_test_split\n",
113 |         "xtrain, xtest, ytrain, ytest = train_test_split(X, y,test_size=0.20)\n",
114 |         "\n",
115 |         "print('\\n the total number of training data ',ytrain.shape)\n",
116 |         "print('\\n the total number of testing data ',ytest.shape)"
117 |       ]
118 |     },
119 |     {
120 |       "cell_type": "code",
121 |       "execution_count": null,
122 |       "metadata": {
123 |         "colab": {
124 |           "base_uri": "https://localhost:8080/"
125 |         },
126 |         "id": "Q_djbAkswkdE",
127 |         "outputId": "6d836d87-99cc-49e6-8ff8-fd724866c75d"
128 |       },
129 |       "outputs": [
130 |         {
131 |           "name": "stdout",
132 |           "output_type": "stream",
133 |           "text": [
134 |             "\n",
135 |             " The words or Tokens in the text documents \n",
136 |             "\n",
137 |             "['about' 'am' 'amazing' 'an' 'and' 'awesome' 'beers' 'best' 'boss' 'can'\n",
138 |             " 'dance' 'deal' 'do' 'enemy' 'feel' 'fun' 'good' 'have' 'he' 'horrible'\n",
139 |             " 'house' 'is' 'like' 'love' 'my' 'not' 'of' 'place' 'restaurant'\n",
140 |             " 'sandwich' 'sick' 'sworn' 'these' 'this' 'tired' 'to' 'today' 'tomorrow'\n",
141 |             " 'very' 'view' 'we' 'went' 'what' 'will' 'with' 'work']\n"
142 |           ]
143 |         }
144 |       ],
145 |       "source": [
146 |         "# output of the words or token in the text document\n",
147 |         "import numpy as np\n",
148 |         "from sklearn.feature_extraction.text import CountVectorizer\n",
149 |         "count_vect = CountVectorizer()\n",
150 |         "xtrain_dtm = count_vect.fit_transform(xtrain)\n",
151 |         "xtest_dtm = count_vect.transform(xtest)\n",
152 |         "index = count_vect.get_feature_names_out()\n",
153 |         "print('\\n The words or Tokens in the text documents \\n')\n",
154 |         "print(count_vect.get_feature_names_out())\n",
155 |         "df = pd.DataFrame(xtrain_dtm.toarray(), columns = count_vect.get_feature_names_out())\n",
156 |         "\n"
157 |       ]
158 |     },
159 |     {
160 |       "cell_type": "code",
161 |       "execution_count": null,
162 |       "metadata": {
163 |         "id": "44_Jf596xe5P"
164 |       },
165 |       "outputs": [],
166 |       "source": [
167 |         "from sklearn.naive_bayes import MultinomialNB\n",
168 |         "clf = MultinomialNB()\n",
169 |         "clf.fit(xtrain_dtm,ytrain)\n",
170 |         "predicted = clf.predict(xtest_dtm)"
171 |       ]
172 |     },
173 |     {
174 |       "cell_type": "code",
175 |       "execution_count": null,
176 |       "metadata": {
177 |         "colab": {
178 |           "base_uri": "https://localhost:8080/"
179 |         },
180 |         "id": "0-on1MEGyEmi",
181 |         "outputId": "be3bddba-1013-4773-e40d-256dd608eca2"
182 |       },
183 |       "outputs": [
184 |         {
185 |           "name": "stdout",
186 |           "output_type": "stream",
187 |           "text": [
188 |             "\n",
189 |             " Accuracy of the classifier is  0.75\n",
190 |             "\n",
191 |             " confusion matrix\n",
192 |             "[[2 1]\n",
193 |             " [0 1]]\n",
194 |             "\n",
195 |             " The value of Precision 0.5\n",
196 |             "\n",
197 |             " The value of Recall 1.0\n"
198 |           ]
199 |         }
200 |       ],
201 |       "source": [
202 |         "from sklearn import metrics\n",
203 |         "print('\\n Accuracy of the classifier is ', metrics.accuracy_score(ytest, predicted))\n",
204 |         "print('\\n confusion matrix')\n",
205 |         "print(metrics.confusion_matrix(ytest, predicted))\n",
206 |         "print('\\n The value of Precision', metrics.precision_score(ytest, predicted))\n",
207 |         "print('\\n The value of Recall', metrics.recall_score(ytest, predicted))"
208 |       ]
209 |     }
210 |   ],
211 |   "metadata": {
212 |     "colab": {
213 |       "authorship_tag": "ABX9TyPCyT4YhsJ6FUkq0PzeV/yY",
214 |       "include_colab_link": true,
215 |       "mount_file_id": "1Kv3AyABmnWyNtCSZGAXQlmP8UgG0VajC",
216 |       "provenance": []
217 |     },
218 |     "kernelspec": {
219 |       "display_name": "Python 3",
220 |       "name": "python3"
221 |     },
222 |     "language_info": {
223 |       "name": "python"
224 |     }
225 |   },
226 |   "nbformat": 4,
227 |   "nbformat_minor": 0
228 | }
229 | 


--------------------------------------------------------------------------------
/ML lab/program7.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |   "cells": [
  3 |     {
  4 |       "cell_type": "markdown",
  5 |       "metadata": {
  6 |         "id": "view-in-github",
  7 |         "colab_type": "text"
  8 |       },
  9 |       "source": [
 10 |         "<a href=\"https://colab.research.google.com/github/Niraj-Ramnani/Lab-Record-6th-sem/blob/main/ML%20lab/program7.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
 11 |       ]
 12 |     },
 13 |     {
 14 |       "cell_type": "markdown",
 15 |       "metadata": {
 16 |         "id": "qHpdG_H0Su6f"
 17 |       },
 18 |       "source": [
 19 |         "### Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge toclassify a new sample"
 20 |       ]
 21 |     },
 22 |     {
 23 |       "cell_type": "code",
 24 |       "execution_count": null,
 25 |       "metadata": {
 26 |         "id": "EmRROYJJ6a5u"
 27 |       },
 28 |       "outputs": [],
 29 |       "source": [
 30 |         "import pandas as pd\n",
 31 |         "import numpy as np\n",
 32 |         "df_tennis = pd.read_csv('tennis.csv')\n",
 33 |         "print(df_tennis)"
 34 |       ]
 35 |     },
 36 |     {
 37 |       "cell_type": "code",
 38 |       "execution_count": null,
 39 |       "metadata": {
 40 |         "colab": {
 41 |           "base_uri": "https://localhost:8080/",
 42 |           "height": 36
 43 |         },
 44 |         "id": "8mVt2Hd48FxL",
 45 |         "outputId": "82913713-2b1b-4eeb-e28b-7c70d12c3e1f"
 46 |       },
 47 |       "outputs": [
 48 |         {
 49 |           "data": {
 50 |             "application/vnd.google.colaboratory.intrinsic+json": {
 51 |               "type": "string"
 52 |             },
 53 |             "text/plain": [
 54 |               "'Outlook'"
 55 |             ]
 56 |           },
 57 |           "execution_count": 9,
 58 |           "metadata": {},
 59 |           "output_type": "execute_result"
 60 |         }
 61 |       ],
 62 |       "source": [
 63 |         "df_tennis.keys()[0]"
 64 |       ]
 65 |     },
 66 |     {
 67 |       "cell_type": "code",
 68 |       "execution_count": null,
 69 |       "metadata": {
 70 |         "id": "4SGbEj_A8WCS"
 71 |       },
 72 |       "outputs": [],
 73 |       "source": [
 74 |         "# Entropy of the training data set\n",
 75 |         "from collections import Counter\n",
 76 |         "def entropy_list(a_list):\n",
 77 |         "    cnt = Counter(x for x in a_list)\n",
 78 |         "import math\n",
 79 |         "def entropy_list(a_list):\n",
 80 |         "    cnt = Counter(x for x in a_list)\n",
 81 |         "    num_instances = len(a_list)*1.0\n",
 82 |         "    probs = [x/num_instances for x in cnt.values()]\n",
 83 |         "  # Function to calculate the entropy of the probablity of observation\n",
 84 |         "    return entropy(probs)\n",
 85 |         "def entropy(probs):\n",
 86 |         "    return -sum(p*math.log(p,2) for p in probs if p>0)\n"
 87 |       ]
 88 |     },
 89 |     {
 90 |       "cell_type": "code",
 91 |       "execution_count": null,
 92 |       "metadata": {
 93 |         "id": "7YPIpvaF9C52"
 94 |       },
 95 |       "outputs": [],
 96 |       "source": [
 97 |         "\n",
 98 |         "# import math\n",
 99 |         "# def entropy(probs)\n",
100 |         "# return sum ([-prob*math.log(prob,2) for prob in probs])"
101 |       ]
102 |     },
103 |     {
104 |       "cell_type": "code",
105 |       "execution_count": null,
106 |       "metadata": {
107 |         "id": "HEYY7FYs-G9w"
108 |       },
109 |       "outputs": [],
110 |       "source": [
111 |         "def entropy_of_list(a_list):\n",
112 |         "    print(\"A_list\",a_list)\n",
113 |         "    from collections import Counter\n",
114 |         "    cnt = Counter(x for x in a_list)\n",
115 |         "    print(\"\\n Class : \" , cnt)\n",
116 |         "    print(\"No and Yes Classes : \",a_list.name,cnt)\n",
117 |         "    num_instances = len(a_list)*1.0\n",
118 |         "    print(\"\\n Number of Instances of the Current Sub Class is {0}:\".format(num_instances))\n",
119 |         "    probs = [x/num_instances for x in cnt.values()]\n",
120 |         "    print(\"\\n Class : \", min(cnt),max(cnt))\n",
121 |         "    print(\"\\n Probablities of class {0} is {1} :\" .format(min(cnt),min(probs)))\n",
122 |         "    print(\"\\n Probablities of class {0} is {1} :\" .format(max(cnt),max(probs)))\n",
123 |         "    return entropy(probs)\n",
124 |         "\n",
125 |         "    print(\"\\n INPUT DATA SET FOR ENTROPY CALCULATION :\\n \", df_tennis['PlayTennis'])\n",
126 |         "    total_entropy = entropy_of_list(df_tennis['PlayTennis'])\n",
127 |         "    print(\"\\n Total Entropy of PlayTennis Data Set : \",total_entropy)"
128 |       ]
129 |     },
130 |     {
131 |       "cell_type": "code",
132 |       "execution_count": null,
133 |       "metadata": {
134 |         "colab": {
135 |           "base_uri": "https://localhost:8080/"
136 |         },
137 |         "id": "YLyjq6uZewkK",
138 |         "outputId": "6a468621-58d1-4a45-aefe-4bcf1c93943e"
139 |       },
140 |       "outputs": [
141 |         {
142 |           "name": "stdout",
143 |           "output_type": "stream",
144 |           "text": [
145 |             "Information Gain Calculation of  Outlook\n",
146 |             "Name:  overcast\n",
147 |             "Group:       Outlook Temperature Humidity    Wind Answer\n",
148 |             "2   overcast         hot     high    weak    yes\n",
149 |             "6   overcast        cool   normal  strong    yes\n",
150 |             "11  overcast        mild     high  strong    yes\n",
151 |             "12  overcast         hot   normal    weak    yes\n",
152 |             "Name:  rain\n",
153 |             "Group:     Outlook Temperature Humidity    Wind Answer\n",
154 |             "3     rain        mild     high    weak    yes\n",
155 |             "4     rain        cool   normal    weak    yes\n",
156 |             "5     rain        cool   normal  strong     no\n",
157 |             "9     rain        mild   normal    weak    yes\n",
158 |             "13    rain        mild     high  strong     no\n",
159 |             "Name:  sunny\n",
160 |             "Group:     Outlook Temperature Humidity    Wind Answer\n",
161 |             "0    sunny         hot     high    weak     no\n",
162 |             "1    sunny         hot     high  strong     no\n",
163 |             "7    sunny        mild     high    weak     no\n",
164 |             "8    sunny        cool   normal    weak    yes\n",
165 |             "10   sunny        mild   normal  strong    yes\n",
166 |             "['Answer']\n",
167 |             "Entropy List <function entroy_of_list at 0x794d232c0ea0>\n",
168 |             "DFAGGENT           entropy_of_list  <lambda_0>\n",
169 |             "Outlook                              \n",
170 |             "overcast        -0.000000    0.285714\n",
171 |             "rain             0.970951    0.357143\n",
172 |             "sunny            0.970951    0.357143\n",
173 |             "Info-gain for Outlook is :0.2467498197744391 \n",
174 |             "\n",
175 |             "Information Gain Calculation of  Humidity\n",
176 |             "Name:  high\n",
177 |             "Group:       Outlook Temperature Humidity    Wind Answer\n",
178 |             "0      sunny         hot     high    weak     no\n",
179 |             "1      sunny         hot     high  strong     no\n",
180 |             "2   overcast         hot     high    weak    yes\n",
181 |             "3       rain        mild     high    weak    yes\n",
182 |             "7      sunny        mild     high    weak     no\n",
183 |             "11  overcast        mild     high  strong    yes\n",
184 |             "13      rain        mild     high  strong     no\n",
185 |             "Name:  normal\n",
186 |             "Group:       Outlook Temperature Humidity    Wind Answer\n",
187 |             "4       rain        cool   normal    weak    yes\n",
188 |             "5       rain        cool   normal  strong     no\n",
189 |             "6   overcast        cool   normal  strong    yes\n",
190 |             "8      sunny        cool   normal    weak    yes\n",
191 |             "9       rain        mild   normal    weak    yes\n",
192 |             "10     sunny        mild   normal  strong    yes\n",
193 |             "12  overcast         hot   normal    weak    yes\n",
194 |             "['Answer']\n",
195 |             "Entropy List <function entroy_of_list at 0x794d232c0ea0>\n",
196 |             "DFAGGENT           entropy_of_list  <lambda_0>\n",
197 |             "Humidity                             \n",
198 |             "high             0.985228         0.5\n",
199 |             "normal           0.591673         0.5\n",
200 |             "Info-gain for Humidity is :0.15183550136234136 \n",
201 |             "\n",
202 |             "Information Gain Calculation of  Wind\n",
203 |             "Name:  strong\n",
204 |             "Group:       Outlook Temperature Humidity    Wind Answer\n",
205 |             "1      sunny         hot     high  strong     no\n",
206 |             "5       rain        cool   normal  strong     no\n",
207 |             "6   overcast        cool   normal  strong    yes\n",
208 |             "10     sunny        mild   normal  strong    yes\n",
209 |             "11  overcast        mild     high  strong    yes\n",
210 |             "13      rain        mild     high  strong     no\n",
211 |             "Name:  weak\n",
212 |             "Group:       Outlook Temperature Humidity  Wind Answer\n",
213 |             "0      sunny         hot     high  weak     no\n",
214 |             "2   overcast         hot     high  weak    yes\n",
215 |             "3       rain        mild     high  weak    yes\n",
216 |             "4       rain        cool   normal  weak    yes\n",
217 |             "7      sunny        mild     high  weak     no\n",
218 |             "8      sunny        cool   normal  weak    yes\n",
219 |             "9       rain        mild   normal  weak    yes\n",
220 |             "12  overcast         hot   normal  weak    yes\n",
221 |             "['Answer']\n",
222 |             "Entropy List <function entroy_of_list at 0x794d232c0ea0>\n",
223 |             "DFAGGENT         entropy_of_list  <lambda_0>\n",
224 |             "Wind                               \n",
225 |             "strong         1.000000    0.428571\n",
226 |             "weak           0.811278    0.571429\n",
227 |             "Info-gain for Wind is :0.04812703040826927 \n",
228 |             "\n"
229 |           ]
230 |         }
231 |       ],
232 |       "source": [
233 |         "def information_gain(df,split_attribute_name,target_attribute_name,trace=0):\n",
234 |         "    print(\"Information Gain Calculation of \",split_attribute_name)\n",
235 |         "    df_split = df.groupby(split_attribute_name)\n",
236 |         "    for name,group in df_split:\n",
237 |         "      print(\"Name: \",name)\n",
238 |         "      print(\"Group: \",group)\n",
239 |         "\n",
240 |         "    nobs = len(df.index)*1.0\n",
241 |         "    df_agg_ent = df_split.agg({target_attribute_name:[entropy_of_list,lambda x:len(x)/nobs]})[target_attribute_name]\n",
242 |         "    print([target_attribute_name])\n",
243 |         "    print(\"Entropy List\",entroy_of_list)\n",
244 |         "    print(\"DFAGGENT\",df_agg_ent)\n",
245 |         "    df_agg_ent.columns = ['Entropy','PropObservations']\n",
246 |         "    new_entropy = sum(df_agg_ent['Entropy']*df_agg_ent['PropObservations'])\n",
247 |         "    old_entropy = entropy_of_list(df[target_attribute_name])\n",
248 |         "    return old_entropy - new_entropy\n",
249 |         "print(\"Info-gain for Outlook is :\"+str(information_gain(df_tennis,'Outlook','Answer',trace=0)),\"\\n\")\n",
250 |         "print(\"Info-gain for Humidity is :\"+str(information_gain(df_tennis,'Humidity','Answer',trace=0)),\"\\n\")\n",
251 |         "print(\"Info-gain for Wind is :\"+str(information_gain(df_tennis,'Wind','Answer',trace=0)),\"\\n\")\n"
252 |       ]
253 |     }
254 |   ],
255 |   "metadata": {
256 |     "colab": {
257 |       "provenance": [],
258 |       "include_colab_link": true
259 |     },
260 |     "kernelspec": {
261 |       "display_name": "Python 3",
262 |       "name": "python3"
263 |     },
264 |     "language_info": {
265 |       "codemirror_mode": {
266 |         "name": "ipython",
267 |         "version": 3
268 |       },
269 |       "file_extension": ".py",
270 |       "mimetype": "text/x-python",
271 |       "name": "python",
272 |       "nbconvert_exporter": "python",
273 |       "pygments_lexer": "ipython3",
274 |       "version": "3.12.4"
275 |     }
276 |   },
277 |   "nbformat": 4,
278 |   "nbformat_minor": 0
279 | }


--------------------------------------------------------------------------------
/ML lab/program8.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |   "nbformat": 4,
  3 |   "nbformat_minor": 0,
  4 |   "metadata": {
  5 |     "colab": {
  6 |       "provenance": [],
  7 |       "authorship_tag": "ABX9TyOL68SWyMU1c7cFx1OWONDO",
  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 |         "<a href=\"https://colab.research.google.com/github/Niraj-Ramnani/Lab-Record-6th-sem/blob/main/ML%20lab/program8.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
 27 |       ]
 28 |     },
 29 |     {
 30 |       "cell_type": "code",
 31 |       "execution_count": 1,
 32 |       "metadata": {
 33 |         "id": "-YxwPv-v5Bxm"
 34 |       },
 35 |       "outputs": [],
 36 |       "source": [
 37 |         "from google.colab import drive"
 38 |       ]
 39 |     },
 40 |     {
 41 |       "cell_type": "code",
 42 |       "source": [
 43 |         "drive.mount('/content/drive')"
 44 |       ],
 45 |       "metadata": {
 46 |         "colab": {
 47 |           "base_uri": "https://localhost:8080/"
 48 |         },
 49 |         "id": "r7C5E6wq5Fec",
 50 |         "outputId": "b15143df-e3ff-4210-f1bf-1c49d6faaa2a"
 51 |       },
 52 |       "execution_count": 4,
 53 |       "outputs": [
 54 |         {
 55 |           "output_type": "stream",
 56 |           "name": "stdout",
 57 |           "text": [
 58 |             "Mounted at /content/drive\n"
 59 |           ]
 60 |         }
 61 |       ]
 62 |     },
 63 |     {
 64 |       "cell_type": "code",
 65 |       "source": [
 66 |         "%cd /content/drive/MyDrive/"
 67 |       ],
 68 |       "metadata": {
 69 |         "colab": {
 70 |           "base_uri": "https://localhost:8080/"
 71 |         },
 72 |         "id": "wDJGpHpB5KCM",
 73 |         "outputId": "d7fbf53d-c950-49c7-a343-69036e48560b"
 74 |       },
 75 |       "execution_count": 5,
 76 |       "outputs": [
 77 |         {
 78 |           "output_type": "stream",
 79 |           "name": "stdout",
 80 |           "text": [
 81 |             "/content/drive/MyDrive\n"
 82 |           ]
 83 |         }
 84 |       ]
 85 |     },
 86 |     {
 87 |       "cell_type": "markdown",
 88 |       "source": [
 89 |         "##Write a program to construct aBayesian network considering medical data. Use this model to demonstrate the diagnosis of heart patients using standard Heart Disease Data Set. You can use Java/Python ML library classes/API."
 90 |       ],
 91 |       "metadata": {
 92 |         "id": "OOlAVBXl561C"
 93 |       }
 94 |     },
 95 |     {
 96 |       "cell_type": "code",
 97 |       "source": [
 98 |         "import pandas as pd\n",
 99 |         "data = pd.read_csv('/content/drive/MyDrive/mydata/heartdisease .csv')\n",
100 |         "heart_disease = pd.DataFrame(data)\n",
101 |         "print(heart_disease)"
102 |       ],
103 |       "metadata": {
104 |         "colab": {
105 |           "base_uri": "https://localhost:8080/"
106 |         },
107 |         "id": "I3lpNJcS5YXT",
108 |         "outputId": "668686ce-8b7a-4323-ba1e-0d798217ff80"
109 |       },
110 |       "execution_count": 15,
111 |       "outputs": [
112 |         {
113 |           "output_type": "stream",
114 |           "name": "stdout",
115 |           "text": [
116 |             "    age  Gender  Family  diet  Lifestyle  cholestrol  heartdisease\n",
117 |             "0     0       0       1     1          3           0             1\n",
118 |             "1     0       1       1     1          3           0             1\n",
119 |             "2     1       0       0     0          2           1             1\n",
120 |             "3     4       0       1     1          3           2             0\n",
121 |             "4     3       1       1     0          0           2             0\n",
122 |             "5     2       0       1     1          1           0             1\n",
123 |             "6     4       0       1     0          2           0             1\n",
124 |             "7     0       0       1     1          3           0             1\n",
125 |             "8     3       1       1     0          0           2             0\n",
126 |             "9     1       1       0     0          0           2             1\n",
127 |             "10    4       1       0     1          2           0             1\n",
128 |             "11    4       0       1     1          3           2             0\n",
129 |             "12    2       1       0     0          0           0             0\n",
130 |             "13    2       0       1     1          1           0             1\n",
131 |             "14    3       1       1     0          0           1             0\n",
132 |             "15    0       0       1     0          0           2             1\n",
133 |             "16    1       1       0     1          2           1             1\n",
134 |             "17    3       1       1     1          0           1             0\n",
135 |             "18    4       0       1     1          3           2             0\n"
136 |           ]
137 |         }
138 |       ]
139 |     },
140 |     {
141 |       "cell_type": "code",
142 |       "source": [
143 |         "import pgmpy.models\n",
144 |         "from pgmpy.models import BayesianNetwork\n",
145 |         "model = BayesianNetwork([\n",
146 |         "('age' , 'Lifestyle'),\n",
147 |         "('Gender' , 'Lifestyle'),\n",
148 |         "('Family' , 'heartdisease'),\n",
149 |         "('diet' , 'cholestrol'),\n",
150 |         "('Lifestyle' , 'diet'),\n",
151 |         "('cholestrol' , 'heartdisease'),\n",
152 |         "('diet' , 'cholestrol')\n",
153 |         "\n",
154 |         "])\n",
155 |         "\n",
156 |         "from pgmpy.estimators import MaximumLikelihoodEstimator\n",
157 |         "model.fit(heart_disease , estimator=MaximumLikelihoodEstimator)\n",
158 |         "\n",
159 |         "from pgmpy.inference import VariableElimination\n",
160 |         "HeartDisease_infer = VariableElimination(model)"
161 |       ],
162 |       "metadata": {
163 |         "id": "NZz7Wj6w6s7c"
164 |       },
165 |       "execution_count": 18,
166 |       "outputs": []
167 |     },
168 |     {
169 |       "cell_type": "code",
170 |       "source": [
171 |         "print('For age Enter { SuperSeniorCitizen:0, SeniorCitizen:1, MiddleAged:2, Youth:3, Teen:4 } ')\n",
172 |         "print('For Gender Enter { Male:0, Female:1 }')\n",
173 |         "print('For Family History Enter { yes:1, No:0 }')\n",
174 |         "print('For diet Enter { High:0, Medium:1 }')\n",
175 |         "print('For LifeStyle Enter { Athlete:0, Active:1, Moderate:2, Sedentary:3 }')\n",
176 |         "print('For cholesterol Enter { High:0, BorderLine:1, Normal:2 }')\n",
177 |         "\n",
178 |         "q = HeartDisease_infer.query(variables=['heartdisease'], evidence={\n",
179 |         "    'age':int(input('Enter age: ')),\n",
180 |         "    'Gender':int(input('Enter Gender: ')),\n",
181 |         "    'Family':int(input('Enter Family History: ')),\n",
182 |         "    'diet':int(input('Enter diet: ')),\n",
183 |         "    'Lifestyle':int(input('Enter Lifestyle: ')),\n",
184 |         "    'cholestrol':int(input('Enter cholestrol: '))\n",
185 |         "\n",
186 |         "})\n",
187 |         "\n",
188 |         "heart_disease_prob = q.values[1]\n",
189 |         "print(f\"Probability of heart disease (heartdisease = 1): {heart_disease_prob}\")"
190 |       ],
191 |       "metadata": {
192 |         "colab": {
193 |           "base_uri": "https://localhost:8080/"
194 |         },
195 |         "id": "kCtRPq4k88yR",
196 |         "outputId": "8654dc99-4802-45bb-988c-8b3b5fa6dde2"
197 |       },
198 |       "execution_count": 23,
199 |       "outputs": [
200 |         {
201 |           "output_type": "stream",
202 |           "name": "stdout",
203 |           "text": [
204 |             "For age Enter { SuperSeniorCitizen:0, SeniorCitizen:1, MiddleAged:2, Youth:3, Teen:4 } \n",
205 |             "For Gender Enter { Male:0, Female:1 }\n",
206 |             "For Family History Enter { yes:1, No:0 }\n",
207 |             "For diet Enter { High:0, Medium:1 }\n",
208 |             "For LifeStyle Enter { Athlete:0, Active:1, Moderate:2, Sedentary:3 }\n",
209 |             "For cholesterol Enter { High:0, BorderLine:1, Normal:2 }\n",
210 |             "Enter age: 1\n",
211 |             "Enter Gender: 1\n",
212 |             "Enter Family History: 1\n",
213 |             "Enter diet: 1\n",
214 |             "Enter Lifestyle: 1\n",
215 |             "Enter cholestrol: 1\n",
216 |             "Query result: \n",
217 |             "+-----------------+---------------------+\n",
218 |             "| heartdisease    |   phi(heartdisease) |\n",
219 |             "+=================+=====================+\n",
220 |             "| heartdisease(0) |              1.0000 |\n",
221 |             "+-----------------+---------------------+\n",
222 |             "| heartdisease(1) |              0.0000 |\n",
223 |             "+-----------------+---------------------+\n",
224 |             "Probability of heart disease (heartdisease = 1): 0.0\n"
225 |           ]
226 |         }
227 |       ]
228 |     },
229 |     {
230 |       "cell_type": "code",
231 |       "source": [],
232 |       "metadata": {
233 |         "id": "9tHNofbM-ib8"
234 |       },
235 |       "execution_count": null,
236 |       "outputs": []
237 |     }
238 |   ]
239 | }


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/Python lab/new.c:
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1 | printf("hello")


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/Python lab/program01.py:
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 1 | # AIM : Write a program to demonstratebasic data type in python.
 2 | a = 5
 3 | print("value of a is " , a ," it is type of " , type(a))
 4 | b = 5.5
 5 | print("value of a is " , b ," it is type of " , type(b))
 6 | c = "messi"
 7 | print("value of c is " , c ," it is type of " , type(c))
 8 | d = True
 9 | print("value of d is " , d ," it is type of " , type(d))
10 | e = (1,2,3)
11 | print("value of e is " , e ," it is type of " , type(e))
12 | f = [4,5,6]
13 | print("value of f is " , f ," it is type of " , type(f))
14 | g = {"name":"messi", "age":37}
15 | print("value of g is " , g ," it is type of " , type(g))
16 | h = {1,1,4,2}
17 | print("value of h is " , h ," it is type of " , type(h))
18 | 
19 | 


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/Python lab/program02-a.py:
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 1 | # Aim :  Write a program to compute distance between two points taking input from the user
 2 | import math as m
 3 | print("For first point enter the values for the x and y cordinate")
 4 | x1 = float(input())
 5 | y1 = float(input())
 6 | print("For second point enter the values for the x and y cordinate")
 7 | x2 = float(input())
 8 | y2 = float(input())
 9 | res = m.sqrt((x2 - x1)**2 + (y2 -y1)**2)
10 | print("Distance between the two point is " , res)


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/Python lab/program02-b.py:
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1 | # Aim : Write a program add.py that takes 2 numbers as command line arguments and prints its sum.
2 | import sys
3 | num1 = int(sys.argv[1])
4 | num2 = int(sys.argv[2])
5 | print("Sum of num1 and num2 is " , (num1 + num2))


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/Python lab/program03-a.py:
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1 | #  Write a Program for checking whether the givennumber is an even number or not.
2 | num = int(input("Enter a number "))
3 | if(num % 2 == 0):
4 |      print("Given number is an even number ")
5 | else:
6 |      print("Given number is a odd number ")


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/Python lab/program03-b.py:
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1 | # Aim : Using a for loop, write a program that prints out the decimal equivalents of 1/2, 1/3, 1/4, . . . , 1/10
2 | for i in range (2,11) :
3 |      num = 1/i
4 |      print(f"1/{i} = {num:.2f}")


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/Python lab/program04-a.py:
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1 | # Write a Program to demonstrate list and tuple in python.
2 | list = [1,2,2,3]
3 | list.append(4)
4 | list.remove(2)
5 | print("Values in list are : " ,list)
6 | tuple = (1,2,3)
7 | print("First element of the tuple is ",tuple[0])
8 | print("Values in tuple are : " , tuple)


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/Python lab/program04-b.py:
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1 | # Aim : Write a program using a for loop that loops over a sequence.
2 | s = (1,2,3,4,5)
3 | for it in s:
4 |      print(it)


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/Python lab/program04-c.py:
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1 | # Aim : Write a program using a while loop that asks the user for a number, and prints a countdown from that number to zero.
2 | num = int(input("Enter the number for the countdown "))
3 | while(num>=0):
4 |      print(num)
5 |      num -=1


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/Python lab/program05-a.py:
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 1 | # Aim : Find the sum of all the primes below two million
 2 | sum = 0
 3 | for i in range (2,2000000):
 4 |      is_prime = True
 5 |      for j in range (2,int((i**0.5))+1):
 6 |           if(i%j==0):
 7 |                is_prime = False
 8 |                break
 9 |      if(is_prime):
10 |           sum = sum + i
11 | print("sum of all the primes below two million ",sum)
12 |      


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/Python lab/program05-b.py:
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 1 | # Aim : By considering the terms in the Fibonacci sequence whose values do not exceed four million, WAP to find the sum of the even-valued terms.
 2 | a,b = 0,1
 3 | sum = 0
 4 | while(b<=4000000):
 5 |      if(b%2==0):
 6 |            sum += b
 7 |      c = a+ b
 8 |      a = b
 9 |      b = c
10 | print("Sum of even sequence below four million in fibonacci sequence " , sum )


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/Python lab/program06-a.py:
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1 | # AIM :  Write a program to count the numbers of characters in the string and store them in a dictionary data structure
2 | string = input("Enter a String : ")
3 | char_count = {}
4 | for char in string:
5 |      if char in char_count:
6 |           char_count[char]+=1
7 |      else:
8 |           char_count[char] = 1
9 | print("count of the characters for the string " , char_count)


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/Python lab/program06-b.py:
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 1 | # AIM :  Write a program to use split and join methods in the string and trace a birthday of a person with a dictionary data structure
 2 | b_day = input ("Enter your birth day (dd mm yy) : ")
 3 | string = b_day.split()
 4 | dict = {
 5 |      "date": string[0],
 6 |      "month" : string[1],
 7 |      "year" : string[2]
 8 | }
 9 | 
10 | it = []
11 | for key , value in dict.items():
12 |     it = it + [key +" " + value]
13 | res = ", ".join(it)
14 | 
15 | print(res)
16 | 


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/Python lab/program07.py:
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 1 | # Write a program to count frequency of characters in a given file. Can you use character frequency to tell whether the given file is a Python program file, C program file or a text file?
 2 | 
 3 | char_freq = {}
 4 | 
 5 | 
 6 | filepath = input("Enter file path: ")
 7 | 
 8 | with open(filepath, 'r') as file:
 9 |     for line in file:
10 |         for char in line:
11 |             if char in char_freq: char_freq[char] += 1
12 |             else: char_freq[char] = 1
13 | 
14 | for ch, cnt in char_freq.items():
15 |     print(ch, ":", cnt)
16 | 
17 | python_keywords = ['def', 'import', 'self', 'print', 'and', 'class']
18 | c_keywords = ['#include', 'int', 'void', 'printf', 'scanf', 'main']
19 | 
20 | with open(filepath, 'r') as file:
21 |         content = file.read().lower()
22 |         
23 |        
24 |         python_count = sum(1 for word in python_keywords if word in content)
25 |         c_count = sum(1 for word in c_keywords if word in content)
26 | if python_count > c_count :
27 |     print("It is a Python file")
28 | elif c_count > python_count : print("It is a  C file")
29 | else: print("it is  a text file")


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/Python lab/program08-a.py:
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1 | filepath = input("Enter file path: ")
2 | 
3 | with open(filepath, 'r') as file:
4 |     for line in file:
5 |         rev_line = line.rstrip()[::-1]  
6 |         print("original : " + line.rstrip())
7 |         print("reverse : "+  rev_line)


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/Python lab/program08-b.py:
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 1 | filepath = input("Enter file path: ")
 2 | 
 3 | 
 4 | char_count = 0
 5 | word_count = 0 
 6 | line_count = 0
 7 | 
 8 | 
 9 | with open(filepath, 'r' ) as file:
10 |     for line in file:
11 |         line_count += 1
12 |         char_count += len(line)
13 |         word_count += len(line.split())
14 | 
15 | 
16 | print("Number of lines     :", line_count)
17 | print("Number of words     :", word_count)
18 | print("Number of characters:", char_count)
19 | 


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/Python lab/program09-a.py:
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 1 | # Write a function nearly equal to test whether two strings are nearly equal. Two strings a andb are nearly equal when a can be generated by a single mutation on.
 2 | def str_equal(str1, str2):
 3 |     if abs(len(str1) - len(str2)) > 1:
 4 |         return False
 5 | 
 6 |     i = j = 0
 7 |     count = 0
 8 | 
 9 |     while i < len(str1) and j < len(str2):
10 |         if str1[i] != str2[j]:
11 |             count += 1
12 |             if count > 1:
13 |                 return False
14 |             if len(str1) == len(str2):
15 |                 i += 1
16 |                 j += 1
17 |             elif len(str1) > len(str2):
18 |                 i += 1
19 |             else:
20 |                 j += 1
21 |         else:
22 |             i += 1
23 |             j += 1
24 | 
25 |    
26 | 
27 |     return count <= 1
28 | 
29 | str1 = input("Enter first string: ")
30 | str2 = input("Enter second string: ")
31 | 
32 | if str_equal(str1, str2):
33 |     print("Strings are nearly equal.")
34 | else:
35 |     print("Strings are not equal.")
36 | 


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/Python lab/program09-b.py:
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1 | #  Write function to compute gcd, lcm of two numbers. Each function shouldn’t exceed one line.
2 | import math 
3 | gcd = lambda a, b: math.gcd(a, b)
4 | lcm = lambda a, b: abs(a * b) // math.gcd(a, b)
5 | a = int(input("Enter first number: "))
6 | b = int(input("Enter second number: "))
7 | print("GCD of", a, "and", b, "is:", gcd(a, b)) 
8 | print("LCM of", a, "and", b, "is:", lcm(a, b))
9 | 


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/Python lab/program10-a.py:
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 1 | # Write a program to implement Merge sort.
 2 | def merge_sort(arr):
 3 |      if len(arr) <= 1:
 4 |           return arr
 5 |      mid = len(arr) // 2
 6 |      left_half = merge_sort(arr[:mid])
 7 |      right_half = merge_sort(arr[mid:])
 8 |      return merge(left_half, right_half)
 9 | 
10 | 
11 | def merge(left, right):
12 |      res = []
13 |      i = j = 0
14 |      while i < len(left) and j < len(right):
15 |           if left[i] < right[j]:
16 |                res.append(left[i])
17 |                i += 1
18 |           else:
19 |                res.append(right[j])
20 |                j += 1
21 |      res.extend(left[i:])
22 |      res.extend(right[j:])
23 |      return res
24 | n = int (input("Enter number of elements: "))
25 | arr = []
26 | print("Enter elements:")
27 | for i in range(n):
28 |     arr.append(int(input()))
29 | print("Unsorted array:", arr) 
30 | arr = merge_sort(arr)
31 | print("Sorted array:", arr)


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/Python lab/program10-b.py:
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 1 | #Write a program to implement Selection sort, Insertion sort
 2 | def selection_sort(arr):
 3 |      n = len(arr)
 4 |      for i in range (n):
 5 |           min = i
 6 |           for j in range (i +1 , n):
 7 |                if arr[j] < arr[min]:
 8 |                     min = j
 9 |           arr[i],arr[min] = arr[min],arr[i]
10 |      return arr
11 | def insertion_sort(arr):
12 |      n = len(arr)
13 |      for i in range (1,n):
14 |           key = arr[i]
15 |           j = i-1
16 |           while j>=0 and arr[j]> key:
17 |                arr[j+1] = arr[j]
18 |                j -= 1
19 |           arr[j+1] = key
20 |      return arr
21 | n = int(input("Enter number of elements "))
22 | print("Enter the elements of the array ")
23 | arr = []
24 | for i in range (n):
25 |      arr.append(int(input()))
26 | print("Unsorted array " , arr)
27 | s_arr = selection_sort(arr)
28 | print("array after selction sort " , s_arr)
29 | i_arr = insertion_sort(arr)
30 | print("array after selction sort " , i_arr)


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/Python lab/pythonlab.pdf:
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https://raw.githubusercontent.com/Niraj-Ramnani/Lab-Record-6th-sem/333ed742d31d32b8c3e384d6dd4875e6c204ee81/Python lab/pythonlab.pdf


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/Python lab/test.txt:
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1 | he is a boy


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/README.md:
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 1 | 
 2 | # Lab Record - 6th Semester (ACEIT)
 3 | 
 4 | Welcome to the **6th Semester Lab Record** repository! This repository contains all the lab records and assignments for the 6th semester of the **ACEIT (Arya College Of Engineering and I.T.)** program.
 5 | 
 6 | ## 🧑‍💻 About This Repository
 7 | 
 8 | This repository serves as a collection of all the work, code, and lab assignments I’ve completed during the 6th semester. Each lab corresponds to a particular subject, and you can find detailed reports, code files, and explanations for each experiment. The aim is to keep track of my progress, share my work with peers, and build a strong foundation for the next steps in my academic and professional journey.
 9 | 
10 | 
11 | Feel free to explore the folders, dive into the details, and get insights into my approach to problem-solving, coding, and practical implementations.
12 | 
13 | ## 🌐 Connect with Me
14 | 
15 | I’d love to connect with you! Whether you’re a fellow student, professional, or enthusiast, feel free to reach out to me on **LinkedIn**:
16 | 
17 | [Connect with Niraj Ramnani on LinkedIn](https://www.linkedin.com/in/niraj-ramnani/)
18 | 
19 | ## 🚀 Future Plans
20 | 
21 | This repository is constantly evolving, and I plan to continue updating it with:
22 | 
23 | - Additional lab records
24 | - Personal projects related to ML, and programming
25 | - Research and academic papers
26 | - Code snippets and tutorials
27 | 
28 | Stay tuned for more! 👨‍💻
29 | 
30 | ## 📍 License
31 | 
32 | This repository is licensed under the **MIT License**. Feel free to use the code and content for educational purposes, but please give appropriate credit.
33 | 
34 | ---
35 | 
36 | 


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