Do we need hundreds of classifiers to solve real world classification problems
Journal of Machine Learning ResearchPublished 1 January 2014
Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, AmorimDinani
Citations2,174
SJR quartileQ1
SJR score2.02
SNIP3.07
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
We evaluate 179 classifiers arising from 17 families (discriminant analysis, Bayesian, neural networks, support vector machines, decision trees, rule-based classifiers, boosting, bagging, stacking,...
Keywords
Computer Science