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Definition

Logistic Regression

Logistic Regression is a foundational classification algorithm used to predict the probability of a binary target variable by mapping linear inputs to a sigmoid probability curve.

Frequently Asked Questions

How does logistic regression differ from linear regression?

Linear regression predicts continuous numerical outcomes. Logistic regression predicts probabilities between 0 and 1 using a logistic Sigmoid function.

What is the decision boundary in logistic regression?

A threshold probability (typically 0.5) where inputs scoring above are classified as positive, and below as negative.

Quick Facts

  • CategoryFoundational AI
  • Key ApplicationBinary classification, spam detection benchmarks, and probability estimating.

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