I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?

  • 1
    $\begingroup$ K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement? $\endgroup$
    – bkshi
    Commented Feb 9, 2019 at 8:58
  • $\begingroup$ I think the OP actually meant the dataset contains a binary feature. $\endgroup$
    – Louis T
    Commented Feb 9, 2019 at 9:49
  • $\begingroup$ Possible duplicate of K-Means clustering for mixed numeric and categorical data $\endgroup$
    – Louis T
    Commented Feb 9, 2019 at 9:50
  • $\begingroup$ Thanks all for your answers , yes my dataset consists of binary features and I want to use clustering to test new samples $\endgroup$
    – lona
    Commented Feb 11, 2019 at 3:23

1 Answer 1


Delete the label column.

Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.

And k-means only works well on continuous variables anyway.


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