In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

Traffic analysis is a compound of strategies intended to find relationships, patterns,
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …

The massive growth in the scale of data has been observed in recent years being a key
factor of the Big Data scenario. Big Data can be defined as high volume, velocity and variety …

Gene expression data have become increasingly important in machine learning and
computational biology over the past few years. In the field of gene expression analysis …

Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …

Pavement condition information is a significant component in Pavement Management
Systems. The labeling and quantification of the type, severity, and extent of surface cracking …

Subspace distance is an invaluable tool exploited in a wide range of feature selection
methods. The power of subspace distance is that it can identify a representative subspace …

One of the most critical challenges in managing complex diseases like COVID-19 is to
establish an intelligent triage system that can optimize the clinical decision-making at the …

Feature selection is a significant task for data mining and pattern recognition. It aims to
select the optimal feature subset with the minimum redundancy and the maximum …

In multi-label learning, each sample is related to multiple labels simultaneously, and
attribute space of samples is with high-dimensionality. Therefore, the key issue for attribute …