Linear Regression

This module contains an implementation of the Linear Regression algorithm, a fundamental technique in machine learning for predicting a continuous outcome based on input features.

Usage

To use the Linear Regression algorithm, follow these steps:

1. Import the LinearRegression class.
2. Create an instance of the class.
3. Fit the model to your training data using the fit method.
4. Make predictions using the predict method.

Example:

from LinearRegression import LinearRegression

lr_model = LinearRegression()
lr_model.fit(X_train, y_train)
predictions = lr_model.predict(X_test)

Parameters

• learning_rate: The step size for gradient descent.
• n_iterations: The number of iterations for gradient descent.

Installation

To use this module, make sure you have the required dependencies installed:

pip install numpy

Coder

Avdhesh Varshney

Happy Coding 👦