                    axis=1).columns

        if self.VERBOSE:
            print(&#34;training qnets&#34;)
        
        modelneg=Qnet(feature_names=featurenames,alpha=alpha)
        modelneg.fit(Xneg_training)
        modelpos=Qnet(feature_names=featurenames,alpha=alpha)
        modelpos.fit(Xpos_training)
        modelneg.training_index=training_index
        modelpos.training_index=training_index
        
    else:
        featurenames = df_training.columns
        X_training=df_training.values.astype(