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1. Discriminative models are trained to learn the boundaries between classes. They model the conditional probability of a target variable Y (class), given an observation x: P(Y|X=x) (“probability of Y given X=x”). Discriminative models describe the probability for classifying a given example x into a classy E Y. Discriminative models include, for example, logistic regression, conditional random fields, support vector machines, neural networks, random forests, or perceptrons.

Added by DJM Jan 2024