EL之RF(RFC)：利用RF对多分类问题进行建模并评估(六分类+分层抽样)

目录

输出结果

设计思路

核心代码

输出结果

设计思路

核心代码

missCLassError = []
nTreeList = range(50, 2000, 50)
for iTrees in nTreeList:
    depth = None
    maxFeat  = 4 try tweaking
    glassRFModel = ensemble.RandomForestClassifier(n_estimators=iTrees, max_depth=depth, max_features=maxFeat,
                                                 oob_score=False, random_state=531)
 
    glassRFModel.fit(xTrain,yTrain)
 
    prediction = glassRFModel.predict(xTest)
    correct = accuracy_score(yTest, prediction)
 
    missCLassError.append(1.0 - correct)