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Multivariate Pattern Analysis in Python |
Bases: object
Dataset container
The class is useful to combine several Datasets with different origin and type and bind them together. Such a combined dataset can then by used to e.g. pass it to a classifier.
MetaDataset does not permanently duplicate data stored in the dataset it contains. The combined samples matrix is build on demand and samples attribute access is redirected to the first dataset in the container.
Currently operations other than samples or feature selection are not fully supported, e.g. passing a MetaDataset to detrend() will initially result in a detrended MetaDataset, but the combined and detrended samples matrix will be lost after the next call to selectSamples() or selectFeatures(), which freshly pulls samples from all datasets in the container.
Initialize dataset instance
Parameter: | datasets (list) – |
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Perform reverse mapping
Return: | List of results per each used mapper and the corresponding part of the provided val. |
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