Simple Linear Regression

Simple Linear Regression is a linear regression model where we have one dependent and one independent variable.

We need to predict values for the dependent variable as a function of the independent variable.



Formula for Simple Linear Regression:

where

y is the dependent Variable

 is the independent Variable

 is the coefficient (connector between dependent and Independent)

 is the Constant

Code Snippet:

from sklearn.linear_model import LinearRegression

simple_regressor = LinearRegression()

simple_regressor.fit(X_train, y_train)

# Prediction

y_pred = simple_regressor.predict(X_test)

Plot

plt.scatter(X_test, y_test, color = 'red')

plt.plot(X_train, simple_regressor.predict(X_train), color = 'blue')

plt.show()