Metadata-Version: 2.4
Name: nie-ml-labs
Version: 1.0.6
Summary: BIS602 Machine Learning Lab Programs - NIE Mysuru (4NI23IS104)
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: pgmpy

# NIE ML Labs (`nie-ml-labs`)

BIS602 Machine Learning Lab Programs  
**4NI23IS104** | The National Institute of Engineering, Mysuru (VTU)

## Install

```bash
pip install nie-ml-labs
```

Or install locally (editable):

```bash
git clone <your-repo-url>
cd nie_ml_labs
pip install -e .
```

## Usage

```python
import nie_ml_labs

# Lab 1 - ADALINE
from nie_ml_labs import Adaline
import numpy as np
m = Adaline(lr=0.01, epochs=10)
m.fit(np.array([[1,2],[2,3]]), np.array([1,0]))

# Run any lab demo directly
from nie_ml_labs import lab1, lab2, lab3, lab4, lab5, lab6, lab7

lab1.run()   # ADALINE demo
lab2.run()   # FIND-S
lab3.run()   # Candidate Elimination
lab4.run()   # Decision Tree
lab5.run()   # Naive Bayes (Gaussian)
lab6.run()   # Naive Bayes (Sentiment)
lab7.run()   # Bayesian Network

# Use your own CSV
lab4.run(csv_path="path/to/your/data.csv")

# Lab 6 with custom sentences
lab6.run(test_sentences=["This is great", "Horrible experience"])
```

## Labs

| Lab | Algorithm |
|-----|-----------|
| lab1 | ADALINE |
| lab2 | FIND-S |
| lab3 | Candidate Elimination |
| lab4 | Decision Tree (ID3/Entropy) |
| lab5 | Naive Bayes — Gaussian |
| lab6 | Naive Bayes — Text/Sentiment |
| lab7 | Bayesian Network (Heart Disease) |
