logo votingFeatureIntervals

Classification by voting feature intervals. Intervals are constucted around each class for each attribute (basically discretization). Class counts are recorded for each interval on each attribute. Classification is by voting. For more info see: G. Demiroz, A. Guvenir: Classification by voting feature intervals. In: 9th European Conference on Machine Learning, 85-92, 1997.

homepage: weka.sourceforge.net/doc.packages/votingFeatureIntervals
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last release: 6 years ago, first release: 6 years ago
packaging: jar
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