Learning algorithms can be less effective on datasets with an extensive feature space due to
the presence of irrelevant and redundant features. Feature selection is a technique that …

Abstract Distributed Denial of Service (DDoS) attack is one of the biggest cyber threats.
DDoS attacks have evolved in quantity and volume to evade detection and increase …

Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …

In recent years, feature selection research has quickly advanced to keep up with the age of
develo** expert systems. This is because the applications of these systems sometimes …

The prediction of interactions in protein networks is very critical in various biological
processes. In recent years, scientists have focused on computational approaches to predict …

Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …

Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …

Nowadays, microarray data processing is one of the most important applications in
molecular biology for cancer diagnosis. A major task in microarray data processing is gene …

In recent decades, the improvement of computer technology has increased the growth of
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …

Link prediction is a technique to forecast future new or missing relationships between nodes
based on the current network information. However, the link prediction in monoplex …