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. In fact, the data from source domain is always fully available in the training partition whereas the random splits are done on the data 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
Added in version 0.4.
References
- __init__(target_domain, cv)¶
- get_n_splits(X=None, y=None)¶
Return the number of splitting iterations in the cross-validator.
- Parameters:
- Xobject
Ignored, exists for compatibility.
- yobject
Ignored, exists for compatibility.
- Returns:
- n_splitsint
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) or shape (n_vectors, n_ts)
Set of SPD matrices or tangent vectors.
- yndarray, shape (n_matrices,) or shape (n_vectors,)
Extended labels for each matrix or vector.
- Yields:
- trainndarray
The training set indices for that split.
- testndarray
The testing set indices for that split.
