What is the main difference between linear regression and logistic regression?
Linear regression is used to predict the continuous dependent variable using a given set of independent variables. Logistic Regression is used to predict the categorical dependent variable using a given set of independent variables. Linear Regression is used for solving Regression problem.
Should I use linear or logistic regression?
Linear Regression is used to handle regression problems whereas Logistic regression is used to handle the classification problems. Linear regression provides a continuous output but Logistic regression provides discreet output.
What is the difference between logistic and linear regression illustrate with example?
Linear regression is used to estimate the dependent variable in case of a change in independent variables. For example, predict the price of houses. Whereas logistic regression is used to calculate the probability of an event. For example, classify if tissue is benign or malignant.
Is linear regression same as logistic?
Linear Regression is all about fitting a straight line in the data while Logistic Regression is about fitting a curve to the data. Linear Regression is a regression algorithm for Machine Learning while Logistic Regression is a classification Algorithm for machine learning.