Linear Regression

Module: deeprai.models.regression.linear_regression

This module introduces a simple Linear Regression model. Linear Regression is a statistical technique commonly used for modeling and analyzing relationships between two variables.

Class: LinearRegression

A class representation of the linear regression model.

1. Initializer: __init__(self)

Description:

Initializes the LinearRegression class.

Attributes:

• fitted_vals (list): A list to store the results after the model has been fitted. This is primarily the coefficients of the linear equation.

Example:

from deeprai.models.regression.linear_regression import LinearRegression

model = LinearRegression()

2. Method: fit(self, x_vals, y_vals)

Description:

Fit the model to the given x_vals and y_vals using linear regression.

Parameters:

• x_vals (list or np.ndarray): The input values or features.

• y_vals (list or np.ndarray): The output values or labels.

Returns:

• list: Coefficients of the linear equation.

Example:

3. Method: run(self, x_val)

Description:

Use the previously fitted model to predict the output for a given x_val.

Parameters:

• x_val (float): The input value for which the prediction is desired.

Returns:

• float: Predicted value based on the linear regression equation.

Example:

predicted_val = model.run(4)
print(predicted_val)