Explain Logistic Regression.

Explain Logistic Regression.

Approach: Describe linear regression passed through a sigmoid function for classification.

A statistical model used for binary classification. It models the probability that an input belongs to a certain class using the sigmoid function: 1 / (1 + e^-z), where z is a linear combination of features.

Follow-up: What is the decision threshold?

Key concepts: sigmoid, log odds, binary classification.