def set_warm_start(self, warm_start): """ Set the status of `warm_start` of the Classifier. Parameters ---------- warm_start : bool Determines warm starting to allow training to pick up from previous training sessions. """ TimeSeriesClassifier.set_warm_start(self, warm_start) for e in (self.layer_1, self.layer_2): e.set_warm_start(warm_start)
def set_warm_start(self, warm_start): """ Set the status of `warm_start` of the Classifier. Parameters ---------- warm_start : bool Determines warm starting to allow training to pick up from previous training sessions. """ TimeSeriesClassifier.set_warm_start(self, warm_start) estimators = self.estimators_ if hasattr( self, 'estimators_') else self.base_estimators for e in estimators: e.set_warm_start(warm_start)