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skzhang1 2023-01-30 06:01:20 -08:00
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website/docs/Use-Cases/Task-Oriented-AutoML.md
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@ -375,7 +375,7 @@ The data split method for classification can be changed into uniform split by se
For both classification and regression tasks more advanced split configurations are possible:
- time-based split can be enforced if the data are sorted by timestamps, by setting `split_type="time"`,
- group-based splits can be set by using `split_type="group"` while providing the group identifier for each sample through the `groups` argument. This is also shown in an [example notebook](https://github.com/microsoft/FLAML/blob/main/notebook/basics/understanding_cross_validation.ipynb.ipynb).
- group-based splits can be set by using `split_type="group"` while providing the group identifier for each sample through the `groups` argument. This is also shown in an [example notebook](https://github.com/microsoft/FLAML/blob/main/notebook/basics/understanding_cross_validation.ipynb).
More in general, `split_type` can also be set as a custom splitter object, when `eval_method="cv"`. It needs to be an instance of a derived class of scikit-learn
[KFold](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html#sklearn.model_selection.KFold)