python confusion matrix 混淆矩阵
作者:互联网
【2】 混淆矩阵-百度百科
【3】 Python中生成并绘制混淆矩阵(confusion matrix)
【4】 使用python绘制混淆矩阵(confusion_matrix)
示例:
程序摘自【4】。
from sklearn.metrics import confusion_matrix import matplotlib.pyplot as plt import numpy as np def plot_confusion_matrix(cm, labels, title='Confusion Matrix'): plt.imshow(cm, interpolation='nearest', cmap='Blues') plt.title(title) plt.colorbar() xlocations = np.array(range(len(labels))) plt.xticks(xlocations, labels, rotation=90) plt.yticks(xlocations, labels) plt.ylabel('True label') plt.xlabel('Predicted label') label = ["ant", "bird", "cat"] tick_marks = np.array(range(len(label))) + 0.5 y_true = [2, 0, 2, 2, 0, 1] y_pred = [0, 0, 2, 2, 0, 2] cm = confusion_matrix(y_true, y_pred) np.set_printoptions(precision=2) cm_normalized = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis] print(cm_normalized) plt.figure(figsize=(12, 8), dpi=120) ind_array = np.arange(len(label)) x, y = np.meshgrid(ind_array, ind_array) for x_val, y_val in zip(x.flatten(), y.flatten()): c = cm_normalized[y_val][x_val] if c > 0.0: plt.text(x_val, y_val, "%0.2f" % (c,), color='red', fontsize=17, va='center', ha='center') # offset the tick plt.gca().set_xticks(tick_marks, minor=True) plt.gca().set_yticks(tick_marks, minor=True) plt.gca().xaxis.set_ticks_position('none') plt.gca().yaxis.set_ticks_position('none') plt.grid(True, which='minor', linestyle='-') plt.gcf().subplots_adjust(bottom=0.15) plot_confusion_matrix(cm_normalized, label, title='Normalized confusion matrix') # plt.savefig('../Data/confusion_matrix.png', format='png') plt.show()
运行结果:
标签:plt,matrix,cm,python,confusion,label,np 来源: https://www.cnblogs.com/picassooo/p/14412529.html