COMPSs K-means

K-means clustering is a method of cluster analysis that aims to partition ''n'' points into ''k'' clusters in which each point belongs to the cluster with the nearest mean. It follows an iterative refinement strategy to find the centers of natural clusters in the data.

Publisher

[<#ROCrate::Organization https://ror.org/05sd8tv96 @properties={"@id"=>"https://ror.org/05sd8tv96", "@type"=>"Organization", "name"=>"Barcelona Supercomputing Center"}>]

License

https://opensource.org/licenses/Apache-2.0

Contents

• KMeans.java
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  Format: text/plain
• complete_graph.svg
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• kmeans.jar
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  Format: [["application/java-archive", <#ROCrate::ContextualEntity https://www.nationalarchives.gov.uk/PRONOM/x-fmt/412 @properties={"@id"=>"https://www.nationalarchives.gov.uk/PRONOM/x-fmt/412", "@type"=>"WebSite", "name"=>"Java Archive Format"}>]]
• App_Profile.json
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  Format: ["application/json", <#ROCrate::ContextualEntity https://www.nationalarchives.gov.uk/PRONOM/fmt/817 @properties={"@id"=>"https://www.nationalarchives.gov.uk/PRONOM/fmt/817", "@type"=>"WebSite", "name"=>"JSON Data Interchange Format"}>]
• compss_command_line_arguments.txt
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• KMeansDataSet.java
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  Format: text/plain
• KMeansItf.java
  Size: 1638
  Format: text/plain