本文整理汇总了Python中sklearn.tree.DecisionTreeClassifier.classify方法的典型用法代码示例。如果您正苦于以下问题：Python DecisionTreeClassifier.classify方法的具体用法？Python DecisionTreeClassifier.classify怎么用？Python DecisionTreeClassifier.classify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.classify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 classify [as 别名]
print('mean of accuracy:')
print('naive bayes', np.array(results_nbc).mean())
print('decision tree', np.array(results_dtc).mean())
# 2. use test_deals.txt for classification
nbc = NaiveBayesClassifier(dataset)
dtc = DecisionTreeClassifier(dataset)
print('naive bayes classification:')
for text in test_dat:
print(text, nbc.classify(text))
print('decision tree classification:')
for text in test_dat:
print(text, dtc.classify(text))
# other classifiers ...
#########################################enf of task3.py
###########################################task3b.py
""" Classification
The objective of this task is to build a classifier that can tell us whether a new, unseen deal
requires a coupon code or not.
We would like to see a couple of steps: