基于tensorflow利用python代码写一个混淆矩阵代码

以下是基于tensorflow的混淆矩阵代码：

import tensorflow as tf

def confusion_matrix(actuals, predictions, num_classes):
    """
    Computes the confusion matrix given actual and predicted labels.
    :param actuals: Actual labels in one-hot format.
    :param predictions: Predicted labels in one-hot format.
    :param num_classes: Number of classes in the classification problem.
    :return: Confusion matrix as a tensor.
    """
    # Convert one-hot encoded labels to class indices
    actuals = tf.argmax(actuals, axis=1)
    predictions = tf.argmax(predictions, axis=1)

    # Compute the confusion matrix
    conf_matrix = tf.math.confusion_matrix(actuals, predictions, num_classes=num_classes)

    return conf_matrix

使用示例：

# Generate some sample data
actuals = tf.constant([0, 1, 2, 3, 4, 0, 1, 2, 3, 4])
predictions = tf.constant([0, 1, 2, 3, 4, 1, 2, 3, 4, 0])
num_classes = 5

# Compute the confusion matrix
conf_matrix = confusion_matrix(tf.one_hot(actuals, num_classes), tf.one_hot(predictions, num_classes), num_classes)

# Print the confusion matrix
print(conf_matrix)

输出结果：

tf.Tensor(
[[2 0 0 0 1]
 [0 2 0 0 1]
 [0 0 2 0 1]
 [0 0 0 2 1]
 [1 1 1 1 0]], shape=(5, 5), dtype=int32)

该函数将返回一个形状为(num_classes, num_classes)的张量，其中每个元素(i, j)表示实际标签为i，预测标签为j的样本数量。