Difference between linear regression and logistic regression

Question

Accepted Answer

Linear regression is used for predicting continuous values, while logistic regression is used for predicting binary outcomes.

Linear regression is used when the dependent variable is continuous, while logistic regression is used when the dependent variable is binary.
Linear regression predicts the value of a dependent variable based on the value of independent variables, while logistic regression predicts the probability of a binary outcome.
Linear regression uses a linear equation to model the relationship between the dependent and independent variables, while logistic regression uses the logistic function to model the relationship between the dependent and independent variables.

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