python绘制confusion matrix的代码

以下是一个使用Python和matplotlib库绘制混淆矩阵的示例代码：

import numpy as np
import matplotlib.pyplot as plt

def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues):
    """
    This function prints and plots the confusion matrix.
    Normalization can be applied by setting `normalize=True`.
    """
    if normalize:
        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
        print("Normalized confusion matrix")
    else:
        print('Confusion matrix, without normalization')

    print(cm)

    plt.imshow(cm, interpolation='nearest', cmap=cmap)
    plt.title(title)
    plt.colorbar()
    tick_marks = np.arange(len(classes))
    plt.xticks(tick_marks, classes, rotation=45)
    plt.yticks(tick_marks, classes)

    fmt = '.2f' if normalize else 'd'
    thresh = cm.max() / 2.
    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
        plt.text(j, i, format(cm[i, j], fmt),
                 horizontalalignment="center",
                 color="white" if cm[i, j] > thresh else "black")

    plt.tight_layout()
    plt.ylabel('True label')
    plt.xlabel('Predicted label')

# 示例数据
classes = ['cat', 'dog', 'fish']
cm = np.array([[10, 2, 1],
               [3, 15, 2],
               [0, 1, 8]])

# 绘制混淆矩阵
plt.figure()
plot_confusion_matrix(cm, classes)
plt.show()

上述代码将输出一个混淆矩阵图像，如下所示：