Description: In the test preparation process to achieve a K means clustering algorithm, K means clustering principle is: in the training samples to find C a cluster center, each cluster center represents a kind of center. Then the samples are classified to the nearest cluster center with the type. C' s choice is a priori knowledge or experience through the selected. Cluster center is obtained through the iterative algorithm.
File list (Check if you may need any files):
proj10-01\Cmeans.m
.........\mydisplay.m
.........\test.m
.........\testdata.m
.........\testdata.mat
proj10-01
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