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Ensemble Learning: Difference between revisions
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==Bagging== | ==Bagging== | ||
[https://link.springer.com/article/10.1023/A:1018054314350 Bagging Predictors]<br> | |||
Bootstrap aggregation<br> | |||
Idea: Given a sample S, bootstrap from the sample to get m samples S_1,...,S_m.<br> | |||
Then build m classifers from those samples<br> | |||
Your new classifier is a linear combination of those classifiers<br> | |||
==References== | ==References== | ||
* [https://link.springer.com/article/10.1023/A:1007607513941 An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization] | * [https://link.springer.com/article/10.1023/A:1007607513941 An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization] | ||