pyriemann.transfer.TLSplitter¶
- class pyriemann.transfer.TLSplitter(target_domain, cv)¶
Class for handling the cross-validation splits of multi-domain data.
This is a wrapper to sklearn’s cross-validation iterators [1] which ensures the handling of domain information with the data points. In fact, the data from source domain is always fully available in the training partition whereas the random splits are done on the data points from the target domain.
- Parameters:
- target_domainstr
Domain considered as target.
- cvNone | BaseCrossValidator | BaseShuffleSplit, default=None
An instance of a cross validation iterator from sklearn.
Notes
New in version 0.4.
References
- __init__(target_domain, cv)¶
- get_n_splits(X=None, y=None)¶
Returns the number of splitting iterations in the cross-validator.
- Parameters:
- Xobject
Ignored, exists for compatibility.
- yobject
Ignored, exists for compatibility.
- Returns:
- n_splitsint
Returns the number of splitting iterations in the cross-validator.
- split(X, y)¶
Generate indices to split data into training and test set.
- Parameters:
- Xndarray, shape (n_matrices, n_channels, n_channels)
Set of SPD matrices.
- yndarray, shape (n_matrices,)
Extended labels for each matrix.
- Yields:
- trainndarray
The training set indices for that split.
- testndarray
The testing set indices for that split.