Description: KMEANSK Performs K-means clustering given a list of feature vectors and k
The argument k indicates the number of clusters you want the data to be
divided into. data_vecs (N*R) is the set of R dimensional feature
vectors for N data points. Each row in data_vecs gives the R
dimensional vector for a single data point. Each column in data_vecs
refers to values for a particular feature vector for all the N data
points. The output data_idxs is a N*1 vector of integers telling which
cluster number a particular data point belongs to. It also outputs
centroids which is a k*R matrix, where each rows gives the vector for
the cluster center. If we want to segment a color image i into 5
clusters using spacial and color information, we can use this function
as follows:
To Search:
File list (Check if you may need any files):
kmeansK.cpp
kmeansK.m
license.txt
mexutils.h
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