def predict(self, samples):
    ' Predict some data\n\n        Parameters\n        ----------\n\n        samples: np.array, size=(N, C, T)\n                 training samples\n\n        Returns\n        -------\n\n        np.array, size=[N]: prediction\n        '
    features = self.riemannian.features(samples)
    return self.classifier.predict(features)
Predict some data

Parameters
----------

samples: np.array, size=(N, C, T)
         training samples

Returns
-------

np.array, size=[N]: prediction
def predict(self, samples):
    ' Predict some data\n\n        Parameters\n        ----------\n\n        samples: np.array, size=(N, C, T)\n                 training samples\n\n        Returns\n        -------\n\n        np.array, size=[N]: prediction\n        '
    features = self.riemannian.features(samples)
    return self.classifier.predict(features)