ba2173ed970b62da786a8f8628470272b6abc1b9,components/outlier-detection/mahalanobis/OutlierMahalanobis.py,OutlierMahalanobis,send_feedback,#OutlierMahalanobis#Any#Any#Any#Any#,132

Before Change

            metric.append(np.asscalar(np.asarray(c)))
        self.metric = metric
            
        return
    
    
    def metrics(self):
         Return custom metrics.

After Change

            reward (float): the reward
            truth : array with correct value (optional)
        
        _ = super().send_feedback(X,feature_names,reward,truth)
        
        // historical reconstruction errors and predictions
        self._scores.append(self.score)
        self._scores = flatten(self._scores)

Instances