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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.
The text was updated successfully, but these errors were encountered:
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.The text was updated successfully, but these errors were encountered: