画混淆矩阵的python代码
时间: 2023-05-24 17:01:34 浏览: 245
基于python实现的评价模型好坏指标,混淆矩阵等
以下是画混淆矩阵的Python代码:
```python
import itertools
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')
# Example usage:
# from sklearn.metrics import confusion_matrix
# y_true = [...]
# y_pred = [...]
# cnf_matrix = confusion_matrix(y_true, y_pred)
# plot_confusion_matrix(cnf_matrix, classes=class_names,
# normalize=True,
# title='Normalized confusion matrix')
```
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