Logistic regression is a statistical method used for binary classification problems, where the goal is to model the relationship between one or more independent variables (features) and a binary dependent variable (outcome) that can take on two possible values, typically represented as 0 and 1. Unlike ordinary linear regression, which predicts continuous outcomes, logistic regression predicts the probability that a given input falls into one of the two categories.
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