XGBoost Demo

import numpy as np
import pandas as pd
import xgboost as xgb
from sklearn.cross_validation import train_test_split
import os
import csv

#from xgboost.sklearn import XGBClassifier
#from sklearn import cross_validation, metrics   #Additional scklearn functions
#from sklearn.grid_search import GridSearchCV   #Perforing grid search
#
#import matplotlib.pylab as plt
#from matplotlib.pylab import rcParams

#记录程序运行时间
import time
start_time = time.time()

#读入数据
current_dir = os.path.abspath('.')
train = pd.read_csv("train_data.csv")
tests = pd.read_csv("test_data.csv")

params={
'booster':'gbtree',
'objective': 'reg:linear', #多分类的问题
'gamma':0.1,  # 用于控制是否后剪枝的参数,