Overview
Who this competition fits
适合已有结构化订单数据建模经验、愿意使用 PaddlePaddle 2.0 及以上版本的个人参赛者。参赛者应能从用户、订单、商品及付款时间等字段构建特征,并输出用户下个月是否购买的预测概率。
Read the original official blurb
通过品牌商家的历史订单数据构建预测模型,预估用户人群在规定时间内产生购买行为的概率。 Official tags: 购买预测. Sign-ups: 1325.
Resources
What this competition gives you
Taken from the competition's official page.
- DataHistorical order training data and next-month purchase test data
- TutorialPaddleREC official resource repository
- TutorialExploratory data analysis tutorial for purchase prediction
- TutorialTime-window feature construction tutorial
- TutorialUser and product feature engineering tutorial
- TutorialMonthly sales prediction implementation tutorial
- TutorialNotebook creation and execution documentation
Preparation
From registration to a first submission
- 01
PaddlePaddle 2.0+
- 02
订单数据特征工程
- 03
时间滑窗特征
- 04
二分类概率预测
- 05
AUC 优化
- 06
AI Studio Notebook 提交
Before you commit: 主要难点是从经过模拟生成、部分特征含义被隐藏且脱敏的历史订单记录中提取有效的用户购买信号,尤其需要处理付款时间并构造时间滑窗特征。还需在 AI Studio Notebook 中通过命令和 token 提交预测结果及可能要求的源码。
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- Baidu AI Studio
- Last checked
- Not recorded