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KMeans2(samples, nclusters, labels, termcrit) → None
Splits set of vectors by a given number of clusters.
- samples (CvArr) – Floating-point matrix of input samples, one row per sample
- nclusters (int) – Number of clusters to split the set by
- labels (CvArr) – Output integer vector storing cluster indices for every sample
- termcrit (CvTermCriteria) – Specifies maximum number of iterations and/or accuracy (distance the centers can move by between subsequent iterations)
implements a k-means algorithm that finds the
clusters and groups the input samples
around the clusters. On output,
contains a cluster index for
samples stored in the i-th row of the
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