Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …

The advent of connected devices and omnipresence of Internet have paved way for
intruders to attack networks, which leads to cyber-attack, financial loss, information theft in …

Computer clusters with the shared-nothing architecture are the major computing platforms
for big data processing and analysis. In cluster computing, data partitioning and sampling …

Responding to user data deletion requests, removing noisy examples, or deleting corrupted
training data are just a few reasons for wanting to delete instances from a machine learning …

Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …

The controlling factors of unconventional shale productivity by comprehensive analysis of
mineralogy, petrophysics, geochemistry, and geomechanics have not been well understood …

Modern intelligent power grid provides an efficient way of managing energy supply and
consumption while facing numerous security threats at the same time. Both natural and man …

Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

With rapid development of unconventional tight and shale reservoirs, considerable amounts
of data sets are increasing rapidly. Data mining techniques are becoming attractive …

The main aim of this study was to compare the performances of the hybrid approaches of
traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE …