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I was able to convert feature from numerical to categorical and choose impact testing from drop list in supervised modeling. Am I able to do the same in clustering? More precisely, I am using k-means from quick models in LAB from 1 data set. In the dropdown list I have 4 options, I am not sure which one to use.

 

Thank you so much,

Marija
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Hi Marija,

impact-coding (or target encoding) refers to a preprocessing method where the categorical feature in question is encoded by using the target variable. A little more info here: http://contrib.scikit-learn.org/categorical-encoding/targetencoder.html

As you can see, in the context of clustering (unsupervised learning) where no target variable is known, this preprocessing option is not available in DSS. 

I hope this helps!

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