def output_compared_plot(self, path):
        length = len(self.all_f1_score)
        elength = len(self.errors)

        if elength > length:
            ratio = elength / length
            self.all_f1_score = UMath.interpolate(self.all_f1_score, length * ratio)
            self.all_precision = UMath.interpolate(self.all_precision, length * ratio)
            self.all_recall = UMath.interpolate(self.all_recall, length * ratio)
            self.all_reliability = UMath.interpolate(self.all_reliability, length * ratio)

        data = [self.errors, self.all_f1_score, self.all_precision, self.all_recall, self.all_reliability]
        colors = ['m', 'c', 'g', 'b', 'r']
        labels = ["Mean square error", "F1 score", "Precision", "Recall", "Reliability"]

        self.view.plot_data("K-fold cross-validation", data, "Epoch", "Amplitude", colors, labels)
        self.view.show()
        self.view.save(path)
dataset/ETHPy150Open tonybeltramelli/Deep-Spying/server/analytics/modules/classification/RelevanceAssessment.py/RelevanceAssessment.output_compared_plot/original