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- import os
- import pandas as pd
- import xgboost as xgb
- from xgboost.sklearn import XGBClassifier
- # 1. 模型加载
- model = XGBClassifier()
- booster = xgb.Booster()
- booster.load_model('./data/ad_xgb.model')
- model._Booster = booster
- # 2. 预测:ad_status = 0, 不出广告
- df_0 = pd.read_csv('./data/predict_data/predict_data_0.csv')
- columns_0 = df_0.columns.values.tolist()
- y_pred_proba_0 = model.predict_proba(df_0[columns_0[2:]])
- df_0['y_0'] = y_pred_proba_0
- # 3. 预测:ad_status = 1, 不出广告
- df_1 = pd.read_csv('./data/predict_data/predict_data_1.csv')
- columns_1 = df_1.columns.values.tolist()
- y_pred_proba_1 = model.predict_proba(df_1[columns_1[2:]])
- df_0['y_1'] = y_pred_proba_1
- # 4. merge 结果
- res_df = pd.merge(df_0, df_1, how='left', on=['apptype', 'mid', 'videoid'])
- print(res_df.head())
- res_df['res_predict'] = res_df['y_0'] - res_df['y_1']
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