Ensemble Methods

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Ensemble ML methods build predictive models by inducing several different predictors, called base predictors or base learners. Typically, a base predictor is a very simple model that is not meant to work on its own. The predictions of such simple models are normally not much better than random guesses, which is why they are called weak learners. It is through the aggregation of the different answers from the various base learners that ensemble learning builds strong learners that produce accurate predictions.

Original languageEnglish
Title of host publicationLectures on Intelligent Systems
Place of PublicationCham, Switzerland
PublisherSpringer, Cham
Number of pages6
ISBN (Electronic)978-3-031-17922-8
ISBN (Print)978-3-031-17921-1, 978-3-031-17924-2
Publication statusPublished - 13 Jan 2023

Publication series

NameNatural Computing Series
ISSN (Print)1619-7127


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