本文整理汇总了Python中tree.Node.children[value]方法的典型用法代码示例。如果您正苦于以下问题：Python Node.children[value]方法的具体用法？Python Node.children[value]怎么用？Python Node.children[value]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tree.Node的用法示例。
在下文中一共展示了Node.children[value]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: ID3
# 需要导入模块: from tree import Node [as 别名]
# 或者: from tree.Node import children[value] [as 别名]
def ID3(self, features, attributes):
self.nodeCnt += 1
wholeCnt = len(features)
positiveCnt = self.countPositive(features)
if positiveCnt == wholeCnt:
return Node(-1, 1, {})
elif positiveCnt == 0:
return Node(-1, 0, {})
elif len(attributes) == 0: # return major label
return Node(-1, 1 if positiveCnt/float(wholeCnt) >= self.postiveRatio else 0, {})
else:
candidates = []
maxGain = 0
cnt = 0
for attribute in attributes:
gain, childs = self.computeGain(features, attribute)
print(str(cnt) + ' : ' + str(gain))
cnt += 1
#gain /= self.splitRatio(features, childs)
if gain > maxGain:
maxGain = gain
candidates = []
candidates.append([attribute, childs])
elif gain == maxGain:
candidates.append([attribute, childs])
bestPick = candidates[randint(0, len(candidates)-1)] # [attribute, childs]
print('choose: ' + str(bestPick[0]) + ' ' + self.featureNames[bestPick[0]])
chi = self.computeChiSquaredCriterion(features, bestPick[1])
pValue = 1 - stats.chi2.cdf(chi, len(bestPick[1]) - 1)
print('chi: ' + str(chi) + ' pvalue: ' + str(pValue) )
if pValue > self.chiCriterion: # split stop
return Node(-1, 1 if positiveCnt/float(wholeCnt) >= self.postiveRatio else 0, {})
currentNode = Node(bestPick[0], '', {})
newAttributes = copy.deepcopy(attributes)
newAttributes.remove(bestPick[0])
for i in range(len(self.featureValue[bestPick[0]])):
value = self.featureValue[bestPick[0]][i]
currentNode.children[value] = self.ID3(bestPick[1][i], newAttributes)
return currentNode