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Hello,
Thanks for your input. Please find answers below in italic:
1- Although we have a custom kfold option on the grid search (inner), we don't have the custom option for kfold in train/test (outer) performance eval?
At the moment, the custom kfold option in only available in the inner grid-search for finding hyperparameters. Thanks for the suggestion, we will see if we can add this feature on the outer train/test kfold in the future.
2-How to change the custom code sample on the grid search custom k fold option to allow for GroupKFold, ex: sklearn.model_selection.GroupKFold ?
You can find code samples on the GroupKFold in the code samples of the custom CV code screen. See below:
Note that at the moment it only works with integer columns which are passed as input to the model. We are looking to improve that in the future.
3-for the outer train/test kfold, how to use a custom column with fold if assignment?
See question 1: custom kfold on the train/test is not supported at the moment. Thanks for the input, it would be an interesting feature indeed.
In general, if you want to configure you cross-validation strategy in a custom way that is not available in the visual interface, I suggest exporting one of the visual Machine Learning models as Jupyter notebooks, and use it as a starting base to develop your own code.
Cheers,
Alexandre
Hello,
Thanks for your input. Please find answers below in italic:
1- Although we have a custom kfold option on the grid search (inner), we don't have the custom option for kfold in train/test (outer) performance eval?
At the moment, the custom kfold option in only available in the inner grid-search for finding hyperparameters. Thanks for the suggestion, we will see if we can add this feature on the outer train/test kfold in the future.
2-How to change the custom code sample on the grid search custom k fold option to allow for GroupKFold, ex: sklearn.model_selection.GroupKFold ?
You can find code samples on the GroupKFold in the code samples of the custom CV code screen. See below:
Note that at the moment it only works with integer columns which are passed as input to the model. We are looking to improve that in the future.
3-for the outer train/test kfold, how to use a custom column with fold if assignment?
See question 1: custom kfold on the train/test is not supported at the moment. Thanks for the input, it would be an interesting feature indeed.
In general, if you want to configure you cross-validation strategy in a custom way that is not available in the visual interface, I suggest exporting one of the visual Machine Learning models as Jupyter notebooks, and use it as a starting base to develop your own code.
Cheers,
Alexandre