本文整理汇总了Python中sklearn.tree.DecisionTreeClassifier.fitted方法的典型用法代码示例。如果您正苦于以下问题：Python DecisionTreeClassifier.fitted方法的具体用法？Python DecisionTreeClassifier.fitted怎么用？Python DecisionTreeClassifier.fitted使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.tree.DecisionTreeClassifier的用法示例。
在下文中一共展示了DecisionTreeClassifier.fitted方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: print
# 需要导入模块: from sklearn.tree import DecisionTreeClassifier [as 别名]
# 或者: from sklearn.tree.DecisionTreeClassifier import fitted [as 别名]
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.cross_validation import train_test_split
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn import cross_validation
data = pd.read_csv("C:\\Users\\User\\Desktop\\iris_data.csv")
print(data)
data.features = data[["SepalLength","SepalWidth","PetalLength","PetalWidth"]]
data.targets = data.Class
feature_train, feature_test, target_train, target_test = train_test_split(data.features, data.targets, test_size=.2)
model = DecisionTreeClassifier(criterion='gini')
model.fitted = model.fit(feature_train, target_train)
model.predictions = model.fitted.predict(feature_test)
print(confusion_matrix(target_test, model.predictions))
print(accuracy_score(target_test, model.predictions))
predicted = cross_validation.cross_val_predict(model,data.features,data.targets, cv=10)
print(accuracy_score(data.targets,predicted))