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京东JData算法大赛-高潜用户购买意向预测

Jupyter Notebook 22.17% Python 77.83%

jdata-machine-learning-competetion's Introduction

Jdata-machine-learning-competetion

京东JData算法大赛-高潜用户购买意向预测

Data Division

train_start_date = '2016-03-10'; train_end_date = '2016-04-11'

test_start_date = '2016-04-11'; test_end_date = '2016-04-16'

prediction_start_date = '2016-03-15'; prediction_end_date = '2016-04-16'

Feature Engineering

  • User related features: new_user.py

    • raw features such as age, sex
    • user_browse_num
    • user_addcart_num
    • user_delcart_num
    • user_buy_num
    • user_favor_num
    • user_click_num
    • buy_addcart_ratio
    • buy_browse_ratio
    • buy_click_ratio
    • buy_favor_ratio
  • Item related features: new_item.py

    • raw features such as brand
    • item_browse_num
    • item_addcart_num
    • item_delcart_num
    • item_buy_num
    • item_favor_num
    • item_click_num
    • buy_addcart_ratio
    • buy_browse_ratio
    • buy_click_ratio
    • buy_favor_ratio
    • comment_num
    • has_bad_comment
    • bad_comment_rate
  • Time related features: gen_feat.py

    • accumulate_user_feat
    • accumulate_product_feat
  • Statistic related features:

    • sku_hot_rank
    • brank_hot_rank

Model and Ensemble

model: XGB, LightGBM, Random Forest

Ensemble method: voting

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