helperFuncs.py 文件源码

def plotROC(auc_list,fpr_list,tpr_list):
    mean_tpr = 0.0
    mean_fpr = np.linspace(0,1,100)

    plt.figure(figsize=(5,5))

    for i in range(len(fpr_list)):
        mean_tpr += np.interp(mean_fpr, fpr_list[i], tpr_list[i])
        mean_tpr[0] = 0.0
        plt.plot(fpr_list[i], tpr_list[i], lw=1, label='ROC fold %d (area = %0.2f)' % (i, auc_list[i]))

    plt.plot([0, 1], [0, 1], '--', color=(0.6, 0.6, 0.6), label='Luck')

    mean_tpr /= len(fpr_list)
    mean_tpr[-1] = 1.0
    mean_auc = auc(mean_fpr, mean_tpr)
    plt.plot(mean_fpr, mean_tpr, 'k--', label='Mean ROC (area = %0.2f)' % mean_auc, lw=2)

    plt.xlim([-0.05, 1.05])
    plt.ylim([-0.05, 1.05])
    plt.xlabel('False Positive Rate')
    plt.ylabel('True Positive Rate')
    plt.title('')
    plt.legend(loc="lower right")
    plt.show()

    return mean_auc, mean_fpr, mean_tpr