决策树的算法的使用

# -*- coding: utf-8 -*-"""Created on Mon Aug 21 12:51:31 2017@author: Administrator"""from sklearn.ensemble import RandomForestClassifier import pandas as pdimport numpy as npimport pandas as pdimport xgboost as xgbfrom pandas import DataFrameimport matplotlib.pyplot as plt## 读取训练集的数据train_data = pd.read_table('X_train.txt',header=None,encoding='gb2312',delim_whitespace=True,index_col=0)predict_data= pd.read_table('X_test.txt',header=None,encoding='gb2312',delim_whitespace=True,index_col=0)train_label= pd.read_table('y_train.txt',header=None,encoding='gb2312',delim_whitespace=True,index_col=0)predict_label= pd.read_table('y_test.txt',header=None,encoding='gb2312',delim_whitespace=True,index_col=0)train_label=train_label.reset_index()-1predict_label=predict_label.reset_index()-1predict_label_column=list(predict_label.columns)predict_label.rename(columns={predict_label_column[0]: 'label'}, inplace=True) clf=RandomForestClassifier(n_jobs=3) clf.fit(train_data, train_label)ypred1=clf.predict(predict_data)   ypred1 = DataFrame(ypred1)ypred1_column=list(ypred1.columns)ypred1.rename(columns={ypred1_column[0]: 'label'}, inplace=True) ac_middle=predict_label-ypred1ac_middle_number=ac_middle[ac_middle['label']==0]accurate=float(ac_middle_number.shape[0])/predict_label.shape[0]

对用的参数的调整：
http://blog.csdn.net/u012102306/article/details/52228516

参考的地址：
http://blog.csdn.net/lulei1217/article/details/49583287
http://www.cnblogs.com/downtjs/archive/2013/08/28/3288203.html