What are the Assumptions of the Linear Regression Algorithm?

• There is a linear regression relationship between dependent and independent features.

• All the features are multivariate normally.

• There is very little or no multicollinearity in the dataset.

• There is very little or no autocorrection in the dataset.

• It also assumes that there is homoscedasticity in the dataset.