Cluster 3.0

日期:2013-03-18     浏览:13221    下载:3916     体积:668K     评论:0    



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Cluster 3.0 is an enhanced version of Cluster, which was originally developed by Michael Eisen while at Stanford University. The main improvement consists of the k-means algorithm, which now includes multiple trials to find the best clustering solution. This is crucial for the k-means algorithm to be reliable. The routine for self-organizing maps was extended to include 2D rectangular geometries. The Euclidean distance and the city-block distance were added to the available measures of similarity.

日本学者编写的cluster软件的增强版,增加了K-Means算法,以寻找最佳聚类结果。

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