Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

In the Telecommunication Industry (TCI) customer churn is a significant issue because the
revenue of the service provider is highly dependent on the retention of existing customers. In …

Understanding the importance of the inputs on the output is useful across many tasks. This
work provides an information-theoretic framework to analyse the influence of inputs for text …

The generation of spectral libraries using hyperspectral data allows for the capture of
detailed spectral signatures, uncovering subtle variations in plant physiology, biochemistry …

The debris flow velocity fundamentally determines its intensity, thereby rendering its
prediction a crucial aspect of disaster prevention and control strategies. However, accurate …

Students' emotional state and attention significantly impact how they handle stress and
interact with their studies. These factors are crucial in defining their learning objectives and …

In this study, Response Surface Methodology (RSM) and machine learning models were
used to predict the mechanical properties of recycled aggregate concrete (RAC) containing …

Feature selection (FS) is integral to machine learning applications for selecting a subset of
salient features to improve performance and reduce computational time (CT). An enhanced …

Customer churn can be defined as the phenomenon of customers who discontinue their
relationship with a company. This problem is transversal to many industries, including the …

Anticipating customer churn trends is extremely important in the current competitive
scenario. This allows the company to take preventive measures before churn occurs, as …