3.1. Cross-validation: evaluating estimator performance

Here is a flowchart of typical cross validation workflow in model training.

https://scikit-learn.org/stable/_images/grid_search_workflow.png

3.1.1. Computing cross-validated metrics

3.1.3. A note on shuffling

交差検証のデータ分割の前にシャッフルする

shuffle引数について

This consumes less memory than shuffling the data directly.

To get identical results for each split, set random_state to an integer.

3.1.4. Cross validation and model selection

Cross validation iterators can also be used to directly perform model selection using Grid Search for the optimal hyperparameters of the model.

「交差検証イテレータは、モデルのハイパーパラメタを最適化するグリッドサーチを使ってモデルを選択するのにも直接使える」

3.1.5. Permutation test score