全球AI挑战赛之虚拟股票预测，冠军

import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import Imputer
import numpy as np
from sklearn.decomposition import PCA
from sklearn.ensemble import RandomForestClassifier  
from lightgbm import LGBMClassifier
from xgboost import XGBClassifier
from sklearn.metrics import log_loss
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import train_test_split
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression

def cvPro(train,label):
    x_train,x_test,y_train,y_test = train_test_split(train,label,test_size = 0.3,random_state = 0)
    
    ##xgb
    xgb_clf = XGBClassifier()
    xgb_clf.fit(x_train,y_train)
    xgb_test_y = xgb_clf.predict_proba(x_test)
    xgb_y_lr_1 = [i[1] for i in xgb_test_y]

    loss = log_loss(y_test,xgb_y_lr_1)
    print("log_loss is :&#