Linear regression can be interpreted probabilistically where the model assumes that the target variable is a linear combination of the features and some random error. This error is assumed to be normally distributed. Linear regression finds the coefficients that minimize this error to fit the linear model to the data.

1. Linear Regression(Probabilistic
interpretation)
-by Hitesh Saini

3. • -Thats why Linear Regression model is the natural model for the
Regression problems