mne.decoding.EMS#
- class mne.decoding.EMS[source]#
- Transformer to compute event-matched spatial filters. - This version of EMS [1] operates on the entire time course. No time window needs to be specified. The result is a spatial filter at each time point and a corresponding time course. Intuitively, the result gives the similarity between the filter at each time point and the data vector (sensors) at that time point. - Note - EMS only works for binary classification. - References - Attributes:
 - Methods - fit(X, y)- Fit the spatial filters. - fit_transform(X[, y])- Fit to data, then transform it. - get_params([deep])- Get the estimator params. - set_params(**params)- Set parameters (mimics sklearn API). - transform(X)- Transform the data by the spatial filters. - fit(X, y)[source]#
- Fit the spatial filters. - Parameters:
- Returns:
- selfinstance of EMS
- Returns self. 
 
- selfinstance of 
 - Examples using - fit:
 - fit_transform(X, y=None, **fit_params)[source]#
- Fit to data, then transform it. - Fits transformer to - Xand- ywith optional parameters- fit_params, and returns a transformed version of- X.
 
 
