def test_DecisionTreeRegressor(*data):
test = pd.read_csv("/home/javis/jd2017/jdata/all_test_new429.csv")
test.fillna(0, inplace=True)
test_x = test.drop(['user_id', 'sku_id'], axis=1)
x_train, x_test, y_train, y_test = data
#引入模型
regr = DecisionTreeRegressor(max_depth=100) #相关参数设置
regr.fit_intercept = True
regr.fit(x_train, y_train)
test['pred'] = regr.predict(test_x)
pred1 = test[['user_id', 'sku_id', 'pred']]
pred = pred1.sort_values('pred', ascending=False)[:1300]
#输出结果
pred.to_csv('./sub/DesicionTree_result.csv', index=False)
#预测得分
print regr.feature_importances
print "tracing score:%f" % regr.score(x_train, y_train)
print "testing score:%f" % regr.score(x_test, y_test)
