BFR algorithm: Difference between revisions
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Introduction to the algorithm added from the book "Mining of massive datasets" (by Rajaraman, Anand and Ullman, Jeffrey David). |
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Revision as of 16:42, 18 May 2018
The BFR algorithm, named after its inventors �������������������������������������������������������������������������������������������Bradley, Fayyad and Reina, is a variant of k-means that is designed to cluster data in a high-dimensional Euclidean space. It makes a very strong assumption about the shape of clusters: they must be normally distributed about a centroid. The mean and standard deviation for a cluster may differ for different dimensions, but the dimensions must be independent.