I have a numerical feature called $x$ and a categorical feature called $y$. $y$ is an ordinal feature (A,B,C,D,E,F). I am using label encoding for my y feature and when I am seeing the correlation using matrix heatmap it shows that my $x$ feature has 0.95 correlation with $y$. I am using logistic regression algorithm. Should I drop one of them?
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Yes, you should drop one of them. It is not a good idea to have highly correlated features in a logistic regression model. You should be able to see the model's accuracy improve after the drop.
answered Dec 13, 2022 at 11:52
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