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最近打各种比赛，在这里分享一些General Model，稍微改改就能用的 XGBoost调参大全： http://blog.csdn.net/han_xiaoyang/article/details/52665396 XGBoost 官方API： http://xgboost.readthedocs.io/en/latest//python/python_api.html Preprocess # 通用的预处理框架 import pandas as pd import numpy as np import scipy as sp # 文件读取 def read_csv_file(f, logging=False): print("==========读取数据=========") data = pd.read_csv(f) if logging: print(data.head(5)) print(f, "包含以下列") print(data.columns.values) print(data.describe()) print(data.info()) return data Logistic Regression # 通用的LogisticRegression框架 import pandas as pd import numpy as np from scipy import sparse from sklearn.preprocessing import OneHotEncoder from sklearn.linear_m
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