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I have a dataset with 10,000 observations. 19 Independent and 1 dependent variable(Customer Response). I want to Analyse the importance of the features for predicting customer response(dependent variable).

The dependent variable is the Binary Categorical variable, of 19 Independent Variables, 17 are categorical ( all Nominal ) and 2 are continuous.

How can I find features that are important for predicting customer response(dependent variable) to include them for predicting Customer Response.?

Arvind Reddy
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  • Please see our threads on [logistic regression](https://stats.stackexchange.com/questions/tagged/logistic%2bregression?tab=Votes). Another popular technique is the [Random Forest](https://stats.stackexchange.com/search?tab=votes&q=random%20forest%20importan*). – whuber Sep 27 '21 at 18:13
  • One option is [tag:boruta], which typically uses [tag:random-forest] but can use any estimator that yields a metric of variable importance. – Sycorax Sep 27 '21 at 18:54

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