Ransomware is a relatively new type of intrusion attack, and is made with the objective of
extorting a ransom from its victim. There are several types of ransomware attacks, but the …

Random forest (RF) is a widely used data prediction and variable selection technique.
However, the variable selection aspect of RF can become unreliable when there are more …

In this study, the Variational Bayes (VB) approach was hybridized with the bootstrap prior
procedure to improve the accuracy of subset selection as well as optimizing the algorithm …

This article presents a Bayesian attribute bagging-based extreme learning machine (BAB-
ELM) to handle high-dimensional classification and regression problems. First, the decision …

The Weibull, log-logistic and log-normal distributions represent the heavy-tailed distributions
that are often used in modelling time-to-event data. While the loglogistic and log-normal …

Objective: The occurrence of colon cancer starts in the inner wall of the large intestine. The
survival of colon cancer patients strongly relies on early detection. Diagnosing colon cancer …

Abstract The Artificial Neural Network Autoregressive model (ANN-AR) is a recently adopted
approach for forecasting Naira to the USD exchange rate. The Bayesian Regularized Neural …

Objective: Breast cancer is a leading cause of cancer-related death among women
worldwide, with approximately 2.3 million new cases and 685,000 deaths reported in 2020 …

One UN Sustainable Development Goal focuses on monitoring the presence, growth, and
loss of forests. The cost of tracking progress towards this goal is often prohibitive. Satellite …

This study aims to extend the generalized exponential model (GEM) to include covariates in
the presence of interval-censored data. The maximum likelihood estimator (MLE) was …