Feature subset selection is considered to be a significant task in data mining. There is a
need to develop optimal solutions with higher order of computational efficiency. In this …

Feature subset selection is one of the important problems in a number of fields namely data
mining, machine learning, pattern recognition. It refers to the problem of opting for useful …

Featured Application The paper analyzes the usage and mechanisms of feature selection
methods that are based on swarm intelligence in different application areas. Abstract The …

Feature selection is an essential task in the field of machine learning, data mining, and
pattern recognition, primarily, when we deal with a large number of features. Feature …

Feature selection attempts to find the most discriminative information aiming to design an
accurate learning system. Feature selection has been the focus of interest for a long time …

Feature selection is one of the most important preprocessing steps for a data mining, pattern
recognition or machine learning problem. Finding an optimal subset of features, among all …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

Feature Selection is a pre-processing step in knowledge discovery from data (KDD) which
aims at retrieving relevant data from the database beforehand. It imparts quality to the results …

Feature subset selection (FSS) has received a great deal of attention in statistics, machine
learning, and data mining. Real world data analyzed by data mining algorithms can involve …

Feature selection is a process of representing wanted features based on the requirement
needed by selecting the best subset of a dataset without changing the originality of the …