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Discriminative model

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TL;DR. A model that learns to distinguish between different classes or predict a value based on input features.

Technical Definition

A model that learns to distinguish between different classes or predict a value based on input features.

How it works

Discriminative models focus on learning the boundary between different classes or predicting a specific output directly from input features. They model the conditional probability P(output | features), making them strong for classification and regression tasks. Most supervised learning algorithms, like logistic regression and SVMs, are discriminative.

Related Concepts

  • Classification — A supervised learning task where the model assigns inputs to discrete categories.
  • Supervised Learning — Learning from input–output pairs where each training example carries a correct label.
  • Generative model — A type of machine learning model that can create new data instances similar to the data it was trained on, or estimate the likelihood of a given data point originating from the training distribution.

Further Reading

  • Google ML Glossary