| Linear Regression | Logistic Regression |
| Used for solving Regression problem | Used for solving Classification problems |
| Predict the value of continuous variables | Predict the values of categorical variables |
| Find the best fit line, which can easily predict the output | Find the S-curve, which can easily classify the samples |
| Least square estimation method is used for estimation of accuracy | Maximum likelihood estimation method is used for estimation of accuracy |
| The output must be a continuous value, such as price, age, etc. | The output must be a categorical value such as 0 or 1, Yes or No, etc. |
| It is required that relationship between dependent variable and independent variable must be linear | It is not required to have the linear relationship between the dependent and independent variable |
| There may be some collinearity between the independent variables | There should not be any collinearity between the independent variable |