asa.py 文件源码

def plot_auc(self, estimator, estimator_name, neg, pos):
        try:
            classifier_probas = estimator.decision_function(self.X_test)
        except AttributeError:
            classifier_probas = estimator.predict_proba(self.X_test)[:, 1]

        false_positive_r, true_positive_r, thresholds = metrics.roc_curve(self.y_test, classifier_probas)
        roc_auc = metrics.auc(false_positive_r, true_positive_r)

        label = '{:.1f}% neg:{} pos:{} {}'.format(roc_auc * 100, neg, pos, estimator_name)
        plt.plot(false_positive_r, true_positive_r, label=label)
        plt.plot([0, 1], [0, 1], 'k--')
        plt.xlim([-0.05, 1.0])
        plt.ylim([0.0, 1.05])
        plt.title('ROC score(s)')
        plt.xlabel('False Positive Rate')
        plt.ylabel('True Positive Rate')
        plt.legend(loc='lower right', prop={'size': 10})
        plt.savefig("ROC.png", dpi=300, bbox_inches='tight')
        plt.grid()