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sunnotes / Ali Data Mining

阿里巴巴大数据竞赛

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Ali_Data_Mining

阿里巴巴大数据竞赛

官网

简介

在天猫,每天都会有数千万的用户通过品牌发现自己喜欢的商品,品牌是联接消费者与商品最重要的纽带。本届赛题的任务就是根据用户4个月在天猫的行为日志,建立用户的品牌偏好,并预测他们在将来一个月内对品牌下商品的购买行为。

数据类型

  • 字 段 字段说明 提取说明
  • user_id 用户标记 抽样&字段加密
  • Time 行为时间 精度到天级别&隐藏年份
  • action_type 用户对品牌的行为类型 包括点击、购买、加入购物车、收藏4种行为 (点击:0 购买:1 收藏:2 购物车:3)
  • brand_id 品牌数字ID 抽样&字段加密

用户对任意商品的行为都会映射为一行数据。其中所有商品ID都已汇总为商品对应的品牌ID。用户和品牌都分别做了一定程度的数据抽样,且数字ID都做了加密。所有行为的时间都精确到天级别(隐藏年份)。

评估指标

最后我们用F1-Score 来拟合准确率与召回率,并且大赛最终的比赛成绩排名以F1得分为准。

实现算法

  • 协同过滤
    简单建模,效果很差

  • 逻辑回归
    最好成绩:1111/0.06480648/0.05224964/5.785456

  • 随机森林
    最好成绩:1160/0.05344828/0.04499274/4.885737

  • 贝叶斯 -ing

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