A systematic review of emerging feature selection optimization methods for optimal text classification: the present state and prospective opportunities
Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …
missing value imputation, feature selection (FS), amongst others, are procedures required to …
Binary Horse herd optimization algorithm with crossover operators for feature selection
This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …
Classification framework for faulty-software using enhanced exploratory whale optimizer-based feature selection scheme and random forest ensemble learning
Abstract Software Fault Prediction (SFP) is an important process to detect the faulty
components of the software to detect faulty classes or faulty modules early in the software …
components of the software to detect faulty classes or faulty modules early in the software …
An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
Continuous metaheuristics for binary optimization problems: An updated systematic literature review
For years, extensive research has been in the binarization of continuous metaheuristics for
solving binary-domain combinatorial problems. This paper is a continuation of a previous …
solving binary-domain combinatorial problems. This paper is a continuation of a previous …
COVID-19 detection from CT scans using a two-stage framework
Abstract Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe
acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It may cause serious ailments in …
acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It may cause serious ailments in …
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
DNA microarray technology is the fabrication of a single chip to contain a thousand genetic
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
Feature selection based nature inspired capuchin search algorithm for solving classification problems
Identification of the optimal subset of features for Feature Selection (FS) problems is a
demanding problem in machine learning and data mining. A trustworthy optimization …
demanding problem in machine learning and data mining. A trustworthy optimization …
An efficient binary chaotic symbiotic organisms search algorithm approaches for feature selection problems
Feature selection is one of the main steps in preprocessing data in machine learning, and its
goal is to reduce features by removing additional and noisy features. Feature selection …
goal is to reduce features by removing additional and noisy features. Feature selection …
An enhanced particle swarm optimization with position update for optimal feature selection
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 …
develo** expert systems. This is because the applications of these systems sometimes …