Model Selection¶
sklearn_xarray.model_selection
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class
CrossValidatorWrapper(cross_validator, dim='sample', groupby=None)[source]¶ Wrap an sklearn cross validator for use with xarray.
- Parameters
- cross_validatorsklearn cross-validator
An instance of a cross-validator.
- dimstr
The dimension along which to perform the split.
- groupbystr or list
Name of coordinate or list of coordinates by which the groups are determined.
Methods
get_n_splits(self[, X, y, groups])Returns the number of splitting iterations in the cross-validator.
split(self, X[, y, groups])Generate indices to split data into training and test set.
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get_n_splits(self, X=None, y=None, groups=None)[source]¶ Returns the number of splitting iterations in the cross-validator.
- Parameters
- Xobject
Always ignored, exists for compatibility.
- yobject
Always ignored, exists for compatibility.
- groupsobject
Always ignored, exists for compatibility.
- Returns
- n_splitsint
Returns the number of splitting iterations in the cross-validator.
-
split(self, X, y=None, groups=None)[source]¶ Generate indices to split data into training and test set.
- Parameters
- Xxarray DataArray or Dataset
Training data, where n_samples is the number of samples and n_features is the number of features.
- yarray-like, shape (n_samples,)
The target variable for supervised learning problems.
- groupsarray-like, with shape (n_samples,), optional
Group labels for the samples used while splitting the dataset into train/test set.
- Returns
- trainndarray
The training set indices for that split.
- testndarray
The testing set indices for that split.