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Logistic regression: log-loss and calibrated probabilities

Logistic regression: a linear model with a probabilistic output

The name is misleading—it is a classifier, not a regressor. Logistic regression takes a linear combination of features, passes it through a sigmoid, and yields the probability of class membership. It is the baseline model for any binary classification task and the starting point of every project. It is interpretable, fast, and often well calibrated out of the box.

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