def predict(self, data, training_report=False):
        output = []
        for r in range(0, len(data)):
            label = self.predict_single(data.iloc[r])
            output.append(label)

        label_array = data[[self.class_column]].as_matrix()
        target = list(pd.DataFrame(label_array)[0])

        if training_report:
            self.fit_report['output'] = output
            self.fit_report['target'] = target
            print("Training Fit done.")
            self.report()

        else:
            self.predict_summary['output'] = output
            self.predict_summary['target'] = target

            print("Testing done.")
            self.summary()
Predict the labels for a given data set
dataset/ETHPy150Open LargePanda/LearnPy/learnpy/models/NaiveBayes.py/NaiveBayes.predict