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Hi, I tested the kmeas function with my data it is not giving any error ( i did not checked accuracy), But it is taking lng time… in fact very long. I have a suggestion not regarding the code but regarding the data you r data.

Now what I understand from you code is..

int dimensions = 950173;
int sampleCount = 128;

, Which means in your data you have 128 samples with each sample having a length of 950173? Practically it is very rare case and at such a higher dimension I personally don’t think any clustering algorithm works well.

If you really wanted to work on such a higher dimensionality, please use PCA to reduce the data to lower dimension or skip some of the features from your feature vector. I am sure you will get better results than operating on raw data.