This commit is contained in:
jiangzhonglian
2017-08-23 14:03:58 +08:00

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@@ -250,14 +250,12 @@ def grabTree(filename):
fr = open(filename)
return pickle.load(fr)
if __name__ == "__main__":
def fishTest():
# 1.创建数据和结果标签
myDat, labels = createDataSet()
# print myDat, labels
# # 计算label分类标签的香农熵
# 计算label分类标签的香农熵
# calcShannonEnt(myDat)
# # 求第0列 为 1/0的列的数据集【排除第0列】
@@ -274,4 +272,32 @@ if __name__ == "__main__":
# print classify(myTree, labels, [1, 1])
# 画图可视化展现
dtPlot.createPlot(myTree)
# dtPlot.createPlot(myTree)
def ContactLensesTest():
"""
Desc:
预测隐形眼镜的测试代码
Args:
none
Returns:
none
"""
# 加载隐形眼镜相关的 文本文件 数据
fr = open('input/3.DecisionTree/lenses.txt')
# 解析数据,获得 features 数据
lenses = [inst.strip().split('\t') for inst in fr.readlines()]
# 得到数据的对应的 Labels
lensesLabels = ['age', 'prescript', 'astigmatic', 'tearRate']
# 使用上面的创建决策树的代码,构造预测隐形眼镜的决策树
lensesTree = createTree(lenses, lensesLabels)
print lensesTree
# 画图可视化展现
# dtPlot.createPlot(lensesTree)
if __name__ == "__main__":
fishTest()
# ContactLensesTest()