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K q-flats : ウィキペディア英語版
K q-flats

In data mining and machine learning, k q-flats algorithm 〔Bradley, P S, and O L Mangasarian. 2000. k-Plane Clustering. Journal of Global Optimization 16, no. 1: 23-32. http://www.springerlink.com/index/H51L607707062TN7.pdf.〕
〔Tseng, P. 2000. Nearest q-flat to m points. Journal of Optimization Theory and Applications 105, no. 1: 249–252.〕 is an iterative method which aims to partition m observations into k clusters where each cluster is close to a q-flat, where q is a given integer.
It is a generalization of the k-means algorithm. In k-means algorithm,
clusters are formed in the way that each cluster is close to one point, which is a 0-flat.
k q-flats algorithm gives better clustering result than k-means algorithm
for some data set.
==Description==


抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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