【发布时间】:2021-10-07 08:33:29
【问题描述】:
我编写了以下代码来生成混淆矩阵
from sklearn.naive_bayes import MultinomialNB
mnb=MultinomialNB()
mnb.fit(X_train,Y_train)
sms2="REMINDER FROM O2: To get 2.50 pounds free call credit and details of great offers pls reply 2 this text with your valid name, house no and postcode"
sms="You’ve Won!"
X_test = [str (item) for item in X_test]
Y_pred = mnb.predict(vec.transform(X_test))
from sklearn.metrics import confusion_matrix
mat = confusion_matrix(Y_test, Y_pred)
print(mat)
names =[ "non-spam", "spam"]
print(names)
sns.heatmap(mat, square=True, annot=True, fmt='d', cbar=False,
xticklabels=names, yticklabels=names)
plt.xlabel('Actual [Truth]')
plt.ylabel('Predicted')
plt.show()
它生成了以下混淆矩阵:
我不确定轴是否正确标记
IE。如果 x 轴应该是实际的,y 轴应该是预测的
或者反过来
【问题讨论】:
标签: machine-learning scikit-learn confusion-matrix