Timeline for Regression with Lots of Categorical Variables
Current License: CC BY-SA 4.0
3 events
| when toggle format | what | by | license | comment | |
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| Jan 9, 2019 at 5:21 | comment | added | Odisseo | After using get_dummies I end up with about 25 dummy features and 15 original numeric features. I don’t think it’s that much. In any case, I also tried calculating a Pearson correlation matrix earlier and none of the original features had any correlation with the target variable so I might give up | |
| Jan 9, 2019 at 5:20 | comment | added | Odisseo | Thank you, yeah I definitely used the pandas get_dummies method. In any case, the highest R2 I got was with polynomial features and a GradientBoosting Regressor ad 0.32... all my other models are very low. I am doing some grid search cross validation with different alphas but I think it will be hard to move beyond this limit. | |
| Jan 9, 2019 at 5:12 | history | answered | Yuval Spiegler | CC BY-SA 4.0 |