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In this week's #TidyTuesday video, I go over common methods for handling data with a large number of correlated features. Using #TidyModels I go over general feature elimination methods using recipes. I then explain issues with correlated features and ways to analyze which correlated components to select. I explain different #MachineLearning algorithms that are useful for handling high-dimensional correlated data. I then show how to use domain knowledge and intuition by utilizing model variable importance scores. Finally, I show a brute force method of utilizing recursive feature elimination.
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TidyTuesday: github.com/rfo...
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