The diversity and specificities of today's businesses have leveraged a wide range of
prediction techniques. In particular, churn prediction is a major economic concern for many …

Machine learning methods, like random forest (RF), have shown their superior performance
in various disciplines, but have not been previously applied to the spatial interpolation of …

A novel correlation based memetic framework (MA-C) which is a combination of genetic
algorithm (GA) and local search (LS) using correlation based filter ranking is proposed in …

Predicting students' academic performance has been a research area of interest in recent
years, with many institutions focusing on improving the students' performance and the …

With the rapid development of telecommunication industry, the service providers are inclined
more towards expansion of the subscriber base. To meet the need of surviving in the …

Communicating effectively with customers is a challenge, especially in a context requiring
long-term planning such as the pension sector. Engaging individuals to obtain information …

The principle of parsimony also known as “Ockham's razor” has inspired many theories of
model selection. Yet such theories, all making arguments in favor of parsimony, are based …

The telecommunication industry faces fierce competition to retain customers, and therefore
requires an efficient churn prediction model to monitor the customer's churn. Enormous size …

Customer churn prediction and profiling are two major economic concerns for many
companies. Different learning approaches have been proposed, however the a priori choice …

Spatially continuous predictions of seabed hardness are important baseline environmental
information for sustainable management of Australia's marine jurisdiction. Seabed hardness …