mne.decoding.get_coef

mne.decoding.get_coef(estimator, attr='filters_', inverse_transform=False, *, verbose=None)

Retrieve the coefficients of an estimator ending with a Linear Model.

This is typically useful to retrieve “spatial filters” or “spatial patterns” of decoding models [1].

Parameters:

estimatorobject | None

An estimator from scikit-learn.

attrstr

The name of the coefficient attribute to retrieve, typically 'filters_' (default) or 'patterns_'.

inverse_transformbool

If True, returns the coefficients after inverse transforming them with the transformer steps of the estimator.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

coefarray

The coefficients.

References

[1]

Stefan Haufe, Frank Meinecke, Kai Görgen, Sven Dähne, John-Dylan Haynes, Benjamin Blankertz, and Felix Bießmann. On the interpretation of weight vectors of linear models in multivariate neuroimaging. NeuroImage, 87:96–110, 2014. doi:10.1016/j.neuroimage.2013.10.067.

Examples using mne.decoding.get_coef

Decoding (MVPA)

Decoding (MVPA)

Decoding source space data

Decoding source space data

Linear classifier on sensor data with plot patterns and filters

Linear classifier on sensor data with plot patterns and filters