harryplotter 0.1.0

A simple machine learning package using scikit-learn

MLPredictor

MLPredictor is a simple machine learning package that trains a RandomForest model using the Iris dataset and enables users to make predictions. The package is built using scikit-learn and is intended as a demonstration of packaging Python machine learning projects for distribution.

Features

• Train a RandomForestClassifier on the Iris dataset.
• Make predictions on new data after training.
• Save and load trained models.

Installation

You can install the package via PyPI or from source.

Install from PyPI

pip install harryplotter

Install from Source (GitHub)

git clone https://github.com/RahulSwami01/Harryplotter.git
cd harryplotter
pip install .

Usage

After installation, you can use MLPredictor to train a model and make predictions.

Example: Training and Making Predictions

from mlpredictor import MLPredictor

# Initialize the predictor
predictor = MLPredictor()

# Train the model on the Iris dataset
predictor.train()

# Make a prediction on a sample input
sample_input = [5.1, 3.5, 1.4, 0.2]
prediction = predictor.predict(sample_input)

print(f"Predicted class: {prediction}")