2 papers
stat.ME2025
Estimating the number of household TV profiles based in customer behaviour using Gaussian mixture model averaging
Gabriel R. Palma, Sally McClean, Brahim Allan +2
TV customers today face many choices from many live channels and on-demand services. Providing a personalised experience that saves customers time when discovering content is essen…
stat.ME2022
Profiling Television Watching Behaviour Using Bayesian Hierarchical Joint Models for Time-to-Event and Count Data
Rafael A. Moral, Zhi Chen, Shuai Zhang +4
Customer churn prediction is a valuable task in many industries. In telecommunications it presents great challenges, given the high dimensionality of the data, and how difficult it…