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GlossaryMachine LearningEnsemble Methods

Ensemble Methods

[ɑnˈsɑmbəl ˈmɛθədz]
Machine Learning
Last updated: December 9, 2024

Definition

Combining multiple models to enhance performance.

Detailed Explanation

Ensemble Methods improve predictive performance by aggregating the predictions of multiple models. Techniques like bagging boosting and stacking reduce variance and bias leading to more robust models.

Use Cases

Boosting model accuracy handling complex datasets reducing overfitting competition-winning solutions.

Related Terms

L2 Regularization

A regularization method that adds the squared magnitude of weights as a penalty term to the loss function, preventing large weight values.

Machine Learning

Learning Curve

A plot showing how training and validation scores change with increasing training data size.

Machine Learning

Feature Selection

Selecting the most relevant variables for model training.

Machine Learning