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I have a dataset which has only categorical values. As I came across a few articles people suggested that KNN / Random forest would work for dataset like this. Though in R it couldn't handle as if contains more than 53 categories.

Whereas in Sklearn, I used linear regression against each column to the column which I was predicting. After which I created a weighted average of all the outputs. But I'm pretty sure it's not the right way.

Can anyone suggest a better way?
PS : The dataset contains 4 columns with only categorical values. With 200 - 250 different categories in each column.

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Welcome to the site!

I think the 53 category issue is specific to R's randomForest package. If you're set on using a random forest, try other packages like ranger and Rborist.

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