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GlossaryMachine LearningStacking

Stacking

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

Definition

Combining multiple models using a meta-model for predictions.

Detailed Explanation

Stacking involves training multiple base models and then using a meta-model to combine their outputs. The meta-model learns the best way to integrate predictions for enhanced performance.

Use Cases

Competition solutions complex predictive tasks leveraging diverse models improving accuracy.

Related Terms

Mixture of Experts (MoE)

An ML architecture using multiple specialized sub-models (experts) and a gating mechanism to route inputs.

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Naive Bayes Algorithm

A probabilistic classifier based on applying Bayes' theorem with independence assumptions.

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Neural Networks

Computing systems inspired by the human brain that learn from data.

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