09 Jul '13, 8am


In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Voronoi cells. (wikipedia) What is k-means clustering http://en.wikipedia.org/wiki/K-means_clustering Source code and tutorial https://github.com/id774/kmeans This version in Rubyforge http://rubyforge.org/frs/shownotes.php?release_id=47283 Rubygems https://rubygems.org/gems/kmeans Blog entry (Japanese) http://blog.id774.net/post/ ChangeLog https://github.com/id774/kmeans/blob/master/doc/ChangeLog

Full article: http://rubyforge.org/forum/forum.php?forum_id=41560



rubyforge.org 09 Jul '13, 8am

A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong (naive) indepen...