Category:Ensemble learning
From Wikipedia, the free encyclopedia
Ensemble learning is a type of machine learning that studies algorithms and architectures that build collections, or ensembles, of statistical classifiers that are more accurate than a single classifier.
[edit] External links
- Ensemble Based Systems in Decision Making, R. Polikar, IEEE Circuits and Systems Magazine, vol.6, no.3, pp. 21-45, 2006. A tutorial article on ensemble systems including pseudocode, block diagrams and implementation issues for AdaBoost and other ensemble learning algorithms.
Pages in category "Ensemble learning"
The following 14 pages are in this category, out of 14 total. This list may not reflect recent changes (learn more).
