Hello,
I'm trying to build a model that can split my data into two categories i.e. "Good to Go" & "Not important". As my data do not have any previous responses/column (Response variable) so regular "Supervised" methods won't work for me.
Can anyone suggest how can I utilize unsupervised methods (like, XG Boost, Forest, Boosted Trees) here?
FYI, there is NO predictor variable present in my data.
Thanks,
Hi @Deepvijay ,
check out the following unsupervised clustering methods:
https://community.alteryx.com/t5/Videos/Cluster-Analysis/td-p/117714
Best regards
Phil
