Feature Selection in K-Centroids Analysis

Anthony_A

I have created some clusters based off survey data. I would like to see the Feature Selection or variable importance of each variable in its contribution to the cluster analysis. It doesn't seem like there is an option to view this out of the box.

I am able to do this in R (with the same package Alteryx is using) and have been referencing this documentation here: https://cran.r-project.org/web/packages/FeatureImpCluster/readme/README.html

Does anyone have any ideas on how to get the variable importance in regard to the clusters? I would like to see which variables have the most impact in determining the clusters. 

Thanks!

Anthony_A

I figured out a better way to do this. You'll need to install the FeatureImpCluster library. 

Open K-Centroids Macro
Save a copy (or at least I did)
Open the R tool in the macro and add the following to the bottom: 

library(FeatureImpCluster)#load library
FeatureImp_res <- FeatureImpCluster(clus.sol,as.data.table(the.matrix)) #Use FeatureImpCluster to take the cluster model (clus.sol) and data (the.matrix) to get variable imp.
FeatureImp_df <- as.data.frame(FeatureImp_res$featureImp) #turns features from a list to dataframe
FeatureImp_df_rn <- tibble::rownames_to_column(FeatureImp_df, "Variable") #Adds the variable name to the importance scores
write.Alteryx(FeatureImp_df_rn, 3) #outputs dataframe in output #3

Add a Macro output to the 3rd connection on the R node.

Save and you're up and running. The third output on the K-Centroid Analysis will show the variable importance. 

Disclaimer, I do not have all contingencies covered here. I have come across some situations where one column won't let the variable importance run but the cluster analysis will work just find.