Top 5 Difference between Linear Regression and Logistic Regression

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1. In the case of Linear Regression, the outcome is continuous while in the case of Logistic Regression outcome is discrete (not continuous)
2. To perform Linear regression we require a linear relationship between the dependent and independent variables. But to perform Logistic regression we do not require a linear relationship between the dependent and independent variables.
3. Linear Regression is all about fitting a straight line in the data while Logistic Regression is about fitting a curve to the data.
4. Linear Regression is a regression algorithm for Machine Learning while Logistic Regression is a classification Algorithm for machine learning.
5. Linear regression assumes Gaussian (or normal) distribution of the dependent variable. Logistic regression assumes the binomial distribution of the dependent variable.

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