alteryx / alteryx/predict-customer-churn

Potential data leakage due to some features?

未關閉
#27 0 則留言 0 個 reaction 已指派 0 人 在 GitHub 檢視
主要語言
Jupyter Notebook
星號
427
分支
216
PR 合併指標
30 天內沒有已合併 PR

描述

Firstly, thanks for the detailed notebooks! Learnt a lot from it.

In https://github.com/Featuretools/predict-customer-churn/blob/main/churn/3.%20Feature%20Engineering.ipynb,
I assume that the features `num_25, num_50, num_75, num_985, num_100, and num_unq, etc` represent the number of specific types of transactions (e.g., number of songs played with 25% completion, 50% completion, etc.) for each customer.

Wouldnt using these features (and various transformations/aggregations on it) in the windows lead to data leakage?

Because basically we are using the information from the future or outside the given time window to create features or train a model.

I have a similar use-case where we have few customer columns like `ltv`, `nr_orders` etc which reflect value "as of today". I am not sure how to handle these in the windows that are created.

貢獻指南

這個儲存庫沒有索引到貢獻指南

評估

這個 Issue 還沒有評估資料。

把新 issue 寄到你的電子郵件信箱

精選適合新手參與的 GitHub issue 摘要。