Prediction of Railway Freight Customer Churn Based on Deep Forest

Pages: 479 - 489
Published: Aug 12, 2021
Abstract
With increasingly fierce competition in other transportation markets, the customer churn in railway freight becomes a very serious problem. Facing the high similarity and indistinguishability of railway freight data, the customer churn prediction (CCP) becomes one of the challenging tasks in this industry. In this paper, a deep forest-based model is developed which can achieve better accuracy of churn predicting in railway freight customer and...
Paper Details
Title
Prediction of Railway Freight Customer Churn Based on Deep Forest
Published Date
Aug 12, 2021
Pages
479 - 489
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