Uses of Package
jwat.workloadAnalysis.clustering
Packages that use jwat.workloadAnalysis.clustering
Package
Description
Workload analysis model of JWAT: the observations, variables and parameters of the workload characterization process.
Clustering algorithms of JWAT for identifying similarities in the input data.
Fuzzy k-means clustering algorithm of JWAT (originally coded in Fortran in 1983 and migrated to Java in 2006).
K-means clustering algorithm of JWAT.
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Classes in jwat.workloadAnalysis.clustering used by jwat.workloadAnalysisClassDescriptionClustering algorithm of JWAT for identifying similarities in the workload data.
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Classes in jwat.workloadAnalysis.clustering used by jwat.workloadAnalysis.clusteringClassDescriptionClustering algorithm of JWAT for identifying similarities in the workload data.Information produced by a JWAT clustering algorithm (clusters and centroids).
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Classes in jwat.workloadAnalysis.clustering used by jwat.workloadAnalysis.clustering.fuzzyKMeanClassDescriptionClustering algorithm of JWAT for identifying similarities in the workload data.Information produced by a JWAT clustering algorithm (clusters and centroids).
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Classes in jwat.workloadAnalysis.clustering used by jwat.workloadAnalysis.clustering.kMeanClassDescriptionClustering algorithm of JWAT for identifying similarities in the workload data.Information produced by a JWAT clustering algorithm (clusters and centroids).