classificationViaClustering · A simple meta-classifier that uses a clusterer for classification. For cluster algorithms that use a fixed number of clusterers, like SimpleKMeans, the user has to make sure that the number of clusters to generate are the same as the number of class labels in the dataset in order to obtain a useful model. Note: at prediction time, a missing value is returned if no cluster is found for the instance. The code is based on the 'clusters to classes' functionality of the weka.clusterers.ClusterEvaluation class by Mark Hall.

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• Latest Stable: 1.0.7.jar

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Version		Vulnerabilities	Size	Updated
1.0.x	classificationViaClustering-1.0.7.jar		9.55 KB	Nov 26, 2017
	classificationViaClustering-1.0.6.jar		8.62 KB	May 29, 2017
	classificationViaClustering-1.0.5.jar		8.57 KB	Apr 27, 2017
	classificationViaClustering-1.0.4.jar		8.54 KB	Apr 04, 2017
	classificationViaClustering-1.0.3.jar		8.54 KB	Apr 28, 2014
	classificationViaClustering-1.0.2.jar		8.53 KB	Apr 26, 2012
	classificationViaClustering-1.0.1.jar		8.53 KB	Apr 23, 2012

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weka.classifiers.meta

├─ weka.classifiers.meta.ClassificationViaClustering.class - [JAR]