AttributeError: 'GaussianNB' object has no attribute 'decision_function'
时间: 2023-12-22 21:29:42 浏览: 206
当出现"AttributeError: 'GaussianNB' object has no attribute 'decision_function'"错误时,这意味着你正在尝试在GaussianNB对象上调用'decision_function'方法,但该对象没有该属性。
GaussianNB是朴素贝叶斯分类器的一种实现,它不具备'decision_function'方法。相反,它具有'predict'方法,用于进行分类预测。
如果你想使用'decision_function'方法,你可以考虑使用其他分类器,例如支持向量机(SVM)或逻辑回归(Logistic Regression),它们通常具有'decision_function'方法来计算样本到决策边界的距离。
以下是一个使用GaussianNB和SVM进行分类的示例:
```python
from sklearn.naive_bayes import GaussianNB
from sklearn.svm import SVC
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# 加载数据集
iris = load_iris()
X, y = iris.data, iris.target
# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# 创建并训练GaussianNB分类器
gnb = GaussianNB()
gnb.fit(X_train, y_train)
# 使用GaussianNB进行预测
gnb_pred = gnb.predict(X_test)
gnb_accuracy = accuracy_score(y_test, gnb_pred)
# 创建并训练SVM分类器
svm = SVC()
svm.fit(X_train, y_train)
# 使用SVM进行预测
svm_decision = svm.decision_function(X_test)
svm_pred = svm.predict(X_test)
svm_accuracy = accuracy_score(y_test, svm_pred)
print("GaussianNB accuracy:", gnb_accuracy)
print("SVM accuracy:", svm_accuracy)
```
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