上述代码绘制混淆矩阵实现

要绘制混淆矩阵热力图，可以参考以下代码实现：

import seaborn as sn
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt

def plot_matrix(y_true, y_pred, title_name):
    cm = confusion_matrix(y_true, y_pred)  # 计算混淆矩阵
    ax = sn.heatmap(cm, annot=True, fmt='g', xticklabels=\['1', '2', '3'\], yticklabels=\['1', '2', '3'\])  # 绘制热力图
    ax.set_title(title_name)  # 设置标题
    ax.set_xlabel('predict')  # 设置x轴标签
    ax.set_ylabel('true')  # 设置y轴标签
    plt.show()  # 显示图像

T_test = \[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3\]
adb_pre = \[3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3\]

plot_matrix(T_test, adb_pre, 'example-confusion matrix')

这段代码首先计算了混淆矩阵`cm`，然后使用seaborn的heatmap函数绘制了热力图，其中`annot=True`表示在热力图上显示数字，`fmt='g'`表示显示的数字格式，`xticklabels`和`yticklabels`指定了横纵轴的标签。`plt.show()`用于显示图像。最后，通过调用`plot_matrix`函数并传入真实标签列表`T_test`和预测标签列表`adb_pre`，以及设置标题名字`'example-confusion matrix'`来绘制混淆矩阵热力图。

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