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@maron you are right, I originally used |
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i get the below error |
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I am also getting the same error as billy-odera: |
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I got the Catboost portion of the code to run by removing metric = 'auc' in the evaluate_model method for CatboostOptimizer. However, this makes the score way out of whack (score on default params is 0.984 …). |
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@talperetz: You are not passing the categorical_column_indices to your CatboostOptimizer instances |
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The CatboostOptimizer class is not going to work with the recent version of Catboost as is. First |
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Can you explain where the 3-fold AUC data is coming from (how this is calculated)? I can figure out how to get AUC for validation data (for Catboost) but not for test data. |
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Hi. Could this code word for a dataset which has non numerical features like sex, city, profession ? And if yes, how ? |
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Sure thing. This dataset holds only categorical features. |
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hi,
great notebook, well explained.
i have a few questions: