raining_index=np.random.choice(self.data.index.values,num_training, replace=False)

    self.training_index=training_index
    df_training=self.data.loc[training_index,:]
    df_training = self.synccols(df_training)
    df_test = self.data.loc[[x for x in self.data.index.values
                             if x not in training_index],:][df_training.columns]

    if self.target_label:
    
        df_training_pos=df_training[df_training[self.target_label]==str(self.target_label_positive)]
        df_training