# Linear vs Logistic Regression

->In the event of Linear Regression the result is constant while if there should arise an occurrence of Logistic Regression result is discrete (not nonstop)

->To perform Linear regression we require a linear connection between the reliant and free factors. Yet, to perform Logistic regression we don’t need a linear connection between the needy and free factors.

->Linear Regression is tied in with fitting a straight line in the information while Logistic Regression is tied in with fitting a bend to the information.

->Linear Regression is a regression algorithm for Machine Learning while Logistic Regression is a characterization Algorithm for AI.

->Linear regression expect gaussian (or ordinary) dissemination of ward variable. Logistic regression accept binomial circulation of ward variable.