We train models on multiple time slices of data and refer to this approach as multi-slicing. Our results show that given the same time frame of data, multi-slicing significantly improves churn prediction performance compared to training on the entire data set as one time slice.
Dec 1, 2021 · Our results show that given the same time frame of data, multi-slicing significantly improves churn prediction performance compared to training on the entire ...
Our results show that given the same time frame of data, multi-slicing significantly improves churn prediction performance compared to training on the entire ...
Our results show that given the same time frame of data, multi-slicing significantly improves churn prediction performance compared to training on the entire ...
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Gattermann-Itschert, T., & Thonemann, U. W. (2021). How Training on Multiple Time Slices Improves Performance in Churn Prediction. European Journal of
Feb 21, 2019 · The usual approach, as I understand it, is to take a slice of that historical data at time t and see which users churn in the time interval (t,t ...
Our results show that given the same time frame of data, multi-slicing significantly improves churn prediction performance compared to training on the entire ...
Jul 19, 2024 · Instead of predicting whether or not they'll churn you'll instead predict time to churn. This lets you include some time dependent covariates ...
Missing: slices | Show results with:slices
Nov 24, 2021 · We want to define churn as probability of customer leaving in next 6 months. One of the clients left the company in fifth year of this period.
Missing: multiple | Show results with:multiple
Nov 11, 2022 · How training on multiple time slices improves performance in churn prediction? European Journal of Operational Research, 295(2), 664-674.