本文整理汇总了Python中weka.classifiers.Classifier.filter方法的典型用法代码示例。如果您正苦于以下问题：Python Classifier.filter方法的具体用法？Python Classifier.filter怎么用？Python Classifier.filter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weka.classifiers.Classifier的用法示例。
在下文中一共展示了Classifier.filter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: Filter
# 需要导入模块: from weka.classifiers import Classifier [as 别名]
# 或者: from weka.classifiers.Classifier import filter [as 别名]
data.class_is_last()
# 1. cheating with default filter
fltr = Filter(classname="weka.filters.supervised.attribute.Discretize", options=[])
fltr.inputformat(data)
filtered = fltr.filter(data)
cls = Classifier(classname="weka.classifiers.trees.J48")
evl = Evaluation(filtered)
evl.crossvalidate_model(cls, filtered, 10, Random(1))
cls.build_classifier(filtered)
print("cheating (default): accuracy=%0.1f nodes=%s" % (evl.percent_correct, get_nodes(str(cls))))
# 2. using FilteredClassifier with default filter
cls = FilteredClassifier()
cls.classifier = Classifier(classname="weka.classifiers.trees.J48")
cls.filter = Filter(classname="weka.filters.supervised.attribute.Discretize", options=[])
evl = Evaluation(data)
evl.crossvalidate_model(cls, data, 10, Random(1))
cls.build_classifier(data)
print("FilteredClassifier (default): accuracy=%0.1f nodes=%s" % (evl.percent_correct, get_nodes(str(cls))))
# 3. using FilteredClassifier (make binary)
cls = FilteredClassifier()
cls.classifier = Classifier(classname="weka.classifiers.trees.J48")
cls.filter = Filter(classname="weka.filters.supervised.attribute.Discretize", options=["-D"])
evl = Evaluation(data)
evl.crossvalidate_model(cls, data, 10, Random(1))
cls.build_classifier(data)
print("FilteredClassifier (make binary): accuracy=%0.1f nodes=%s" % (evl.percent_correct, get_nodes(str(cls))))
# 1. cheating with make binary