决策树买不买电脑2_接下来是最后一题,我将给你一些数据,它给出判断目标人群是否购买电脑的训练数据,

from math import log
 
def calcShannonEnt(dataSet):
    numEntries = len(dataSet)  #
    labelCounts = {
   }
    # 以下五行为所有可能分类创建字典
    for featVec in dataSet:
        currentLabel = featVec[-1]  #提取最后一项做为标签
        if currentLabel not in labelCounts.keys():
            labelCounts[currentLabel] = 0
        labelCounts[currentLabel] += 1  # 书中有错
    # 0:{"yes":1} 1:{"yes":2}  2:{"no":1} 3:{"no":2} 4:{"no":3}
    shannonEnt = 0.0
    for key in labelCounts:
        prob = float(labelCounts[key]) / numEntries  # 计算概率
        # 以2为底求对数
        shannonEnt -= prob * log(prob,2) # 递减求和得熵
    return shannonEnt
 
# 手动计算:  Ent = -0.4*log(2,0.4)-0.6*log(2,0.6)
# Ent_mannual = -(0.4 * log(0.4,2)) - (0.6 * log(0.6,2))
# print(Ent_mannual)
 
# 写一个数据集
def createDataSet():
    dataSet = [['<=30', 'high', 'no', 'fair', 'no'],
               ['<=30', 'high', '
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