A non-sequential representation of sequential data for churn prediction

Mark Eastwood, B. Gabrys

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)
Original languageEnglish
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems
EditorsJ.D. Velásquez, S.A. Ríos, R.J. Howlett, L.C. Jain
Place of PublicationBerlin
PublisherSpringer
Pages209-218
ISBN (Print)9783642045943, 0302-9743, 9783642045950
DOIs
Publication statusPublished - 2009

Bibliographical note

The full text is not available from the repository. Please note Mark Eastwood was working at Bournemouth University at the time of publication. This book is volume 5711 in the series Lecture Notes in Computer Science.

Keywords

  • sequential data
  • churn prediction
  • customer retention
  • non-sequential dataset

Cite this

Eastwood, M., & Gabrys, B. (2009). A non-sequential representation of sequential data for churn prediction. In J. D. Velásquez, S. A. Ríos, R. J. Howlett, & L. C. Jain (Eds.), Knowledge-Based and Intelligent Information and Engineering Systems (pp. 209-218). Berlin: Springer. https://doi.org/10.1007/978-3-642-04595-0_26