Journal of Machine Learning Research· 2014Q1
Do we need hundreds of classifiers to solve real world classification problems
- 2,181citations
- Q1SCImago
- 2014year
Short summary
A comprehensive evaluation of 179 classifiers across 17 families reveals that a small subset of ensemble methods (boosting, bagging, stacking) and kernel-based methods (SVMs) consistently outperform others on real-world datasets.
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