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move calc_H_D out for loop #11

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Merged
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May 23, 2020
Merged

move calc_H_D out for loop #11

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5 changes: 3 additions & 2 deletions DecisionTree/DecisionTree.py
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Original file line number Diff line number Diff line change
Expand Up @@ -142,11 +142,12 @@ def calcBestFeature(trainDataList, trainLabelList):
maxG_D_A = -1
#初始化最大信息增益的特征
maxFeature = -1
#1.计算数据集D的经验熵H(D)
H_D = calc_H_D(trainLabelArr)
#对每一个特征进行遍历计算
for feature in range(featureNum):
#“5.2.2 信息增益”中“算法5.1（信息增益的算法）”第一步：
#1.计算数据集D的经验熵H(D)
H_D = calc_H_D(trainLabelArr)

#2.计算条件经验熵H(D|A)
#由于条件经验熵的计算过程中只涉及到标签以及当前特征，为了提高运算速度（全部样本
#做成的矩阵运算速度太慢，需要剔除不需要的部分），将数据集矩阵进行切割
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