clustering with k means

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 ?

• 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? – bkshi Feb 9 '19 at 8:58
• I think the OP actually meant the dataset contains a binary feature. – Louis T Feb 9 '19 at 9:49
• Possible duplicate of K-Means clustering for mixed numeric and categorical data – Louis T Feb 9 '19 at 9:50
• Thanks all for your answers , yes my dataset consists of binary features and I want to use clustering to test new samples – lona Feb 11 '19 at 3:23

1 Answer

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.