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GlossaryMachine LearningBagging

Bagging

[ˈbæɡɪŋ]
Machine Learning
Last updated: December 9, 2024

Definition

An ensemble technique using bootstrap sampling and aggregation.

Detailed Explanation

Bagging or Bootstrap Aggregating builds multiple models from random subsets of the training data and aggregates their predictions. It reduces variance and helps prevent overfitting in high-variance models.

Use Cases

Random Forests (ensemble of decision trees) improving unstable models increasing robustness regression and classification tasks.

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