step_corr() can remove highly correlated continuous variables using Pearson or Spearman correlation analysis. However, prefilter functions for categorical variables were not provided in the
recipes package. I have 20 columns with categorical variables (using one-hot encoding), and I want to remove redundant columns which were correlated with each other. Anyone can give me some advice? Thanks
If you want top remove the entire predictor you would have to write a custom recipe step to do that.
Alternatively, after you create indicator variables with
step_corr() could be applied to remove levels of the factor(s) that have redundant information in them
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