What is the difference between logistic regression and linear regression? How do you decide the threshold?

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Accepted Answer

Logistic regression is used for classification while linear regression is used for regression. Threshold is decided based on the problem.

Logistic regression predicts the probability of an event occurring, while linear regression predicts a continuous outcome.
Logistic regression uses a sigmoid function to map the predicted values between 0 and 1.
Linear regression uses a linear equation to model the relationship between the independent and dependent variables.
The threshold in logistic regression is typically set at 0.5, but it can be adjusted based on the problem and the desired trade-off between precision and recall.
For example, in a binary classification problem where predicting a positive outcome is more important, the threshold can be lowered to increase the recall.

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