Using Clustering for Generating Diversity in Classifier Ensemble
作者： Hamid Parvin , Hosein Alizadeh , Behrouz Minaei-Bidgoli
DOI: 10.4156/JDCTA.VOL3.ISSUE1.PARVIN
关键词:
摘要: In the past decade many new methods were proposed for creating diverse classifiers due to combination. this paper a method constructing an ensemble is which uses clustering technique generate perturbation in training datasets. Main presumption of that algorithm used can find natural groups data feature space. During testing, whose votes are considered as being reliable combined using majority voting. This combination outperforms all considerably on several real and artificial
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