What are the disadvantages of the linear regression Algorithm?

The main disadvantages of linear regression are as follows:

  • Assumption of linearity: It assumes that there exists a linear relationship between the independent variables(input) and dependent variables (output), therefore we are not able to fit the complex problems with the help of a linear regression algorithm.
  • Outliers: It is sensitive to noise and outliers.
  • Multicollinearity: It gets affected by multicollinearity.