第1关：返回分类次数最多的分类名称
python
复制代码
import operator
def majorityCnt(classList):
classCount = {}
for i in classList:
if i not in classCount:
classCount[i] = 0
classCount[i] += 1
sortedClassCount = sorted(classCount.items(), key=operator.itemgetter(1), reverse=True)
return sortedClassCount[0][0]
第2关：创建树函数
python
复制代码
from ex03_lib import majorityCnt,splitDataSet,chooseBestFeatureToSplit
def createTree(dataSet,labels):
classList = [example[-1] for example in dataSet] #获取数据集的所有类别
#### 请补充完整代码 ####
if classList.count(classList[0]) == len(classList):
return classList[0]
if len(dataSet[0]) == 1:
return majorityCnt(classList)
bestFeat = chooseBestFeatureToSplit(dataSet)
bestFeatLabel = labels[bestFeat]
myTree = {bestFeatLabel:{}}
del(labels[bestFeat])
featValues = [example[bestFeat] for example in dataSet]
uniqueVals = set(featValues)
for value in uniqueVals:
subLabels = labels[:]
myTree[bestFeatLabel][value] = createTree(splitDataSet(dataSet, bestFeat, value), subLabels)
#######################
return myTree
第3关：获取叶子节点数目
python
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def getNumLeafs(myTree):
numLeafs = 0
if type(myTree).__name__ == 'dict':
fi = list(myTree.keys())[0]
se = myTree[fi]
for i in se.keys():
if type(se[i]).__name__ == 'dict':
numLeafs += getNumLeafs(se[i])
else:
numLeafs += 1
else:
numLeafs += 1
return numLeafs
第4关：获取树的层数
python
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def getTreeDepth(myTree):
maxDepth = 0
#### 请补充完整代码 ####
fi = list(myTree.keys())[0]
se = myTree[fi]
for i in se.keys():
if type(se[i]).__name__ == 'dict':
thisDepth = 1 + getTreeDepth(se[i])
else:
thisDepth = 1
if thisDepth > maxDepth: maxDepth = thisDepth
#######################
return maxDepth
第5关：注解树节点
python
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import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
#定义决策树决策结果的特征，以字典的形式定义
#下面的字典定义也可写作 decisionNode={boxstyle:'sawtooth',fc:'0.8'}
#boxstyle为文本框的类型，sawtooth是锯齿形，fc是边框线粗细
decisionNode = dict(boxstyle="sawtooth", fc="0.8")
leafNode = dict(boxstyle="round4", fc="0.8")
arrow_args = dict(arrowstyle="<-")
def plotNode(nodeTxt, centerPt, parentPt, nodeType):
#annotate是关于一个数据点的文本
#nodeTxt为要显示的文本，centerPt为文本的中心点，parentPt为指向文本的点
#### 请补充完整代码 ####
createPlot.ax1.annotate(nodeTxt, xy=parentPt, xycoords='axes fraction',
xytext=centerPt, textcoords='axes fraction',
va="center", ha="center", bbox=nodeType, arrowprops=arrow_args )
#######################
def createPlot():
fig = plt.figure(1,facecolor='white') # 定义一个画布，背景为白色
fig.clf() # 把画布清空
#createPlot.ax1为全局变量，绘制图像的句柄，subplot为定义了一个绘图，
#111表示figure中的图有1行1列，即1个，最后的1代表第一个图
#frameon表示是否绘制坐标轴矩形
#### 请补充完整代码 ####
createPlot.ax1 = plt.subplot(111,frameon=False)
plotNode('a decision node',(0.2,0.2),(0.6,0.8),decisionNode)
plotNode('a leaf node',(0.6,0.1),(0.8,0.8),leafNode)
plt.show()
#######################
第6关：绘制树形图
python
复制代码
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from ex03_lib import plotNode,getNumLeafs,getTreeDepth
def plotTree(myTree, parentPt, nodeTxt):
numLeafs = getNumLeafs(myTree) #当前树的叶子数
depth = getTreeDepth(myTree) #没有用到这个变量
firstSides = list(myTree.keys())
firstStr = firstSides[0]
#cntrPt是文本中心点，parentPt指向文本中心点
#### 请补充完整代码 ####
cntrPt = (plotTree.xOff + (1.0 + float(numLeafs))/2.0/plotTree.totalW, plotTree.yOff)
plotMidText(cntrPt, parentPt, nodeTxt) #画分支上的键
plotNode(firstStr, cntrPt, parentPt, decisionNode)
secondDict = myTree[firstStr]
plotTree.yOff = plotTree.yOff - 1.0/plotTree.totalD #从上往下画
for key in secondDict.keys():
#如果是字典则是一个判断（内部）结点
if type(secondDict[key]).__name__=='dict':
plotTree(secondDict[key],cntrPt,str(key))
else: #打印叶子结点
plotTree.xOff = plotTree.xOff + 1.0/plotTree.totalW
plotNode(secondDict[key], (plotTree.xOff, plotTree.yOff), cntrPt, leafNode)
plotMidText((plotTree.xOff, plotTree.yOff), cntrPt, str(key))
plotTree.yOff = plotTree.yOff + 1.0/plotTree.totalD
#######################
def plotMidText(cntrPt, parentPt, txtString):
xMid = (parentPt[0]-cntrPt[0])/2.0 + cntrPt[0]
yMid = (parentPt[1]-cntrPt[1])/2.0 + cntrPt[1]
createPlot.ax1.text(xMid, yMid, txtString, va="center", ha="center", rotation=30)
def createPlot(inTree):
fig = plt.figure(1, facecolor='white')
fig.clf()
#### 请补充完整代码 ####
axprops = dict(xticks=[], yticks=[]) #定义横纵坐标轴
createPlot.ax1 = plt.subplot(111, frameon=False)
plotTree.totalW = float(getNumLeafs(inTree)) #全局变量宽度 = 叶子数
plotTree.totalD = float(getTreeDepth(inTree)) #全局变量高度 = 深度
#图形的大小是0-1 ，0-1
plotTree.xOff = -0.5/plotTree.totalW;
#例如绘制3个叶子结点，坐标应为1/3,2/3,3/3
#但这样会使整个图形偏右因此初始的，将x值向左移一点。
plotTree.yOff = 1.0;
plotTree(inTree, (0.5,1.0), '')
#######################
plt.show()