A comprehensive survey on feature selection in the various fields of machine learning
Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …
data's dimensionality and enhancing any proposed framework's performance. However, in …
A review of the modification strategies of the nature inspired algorithms for feature selection problem
This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …
researchers to guide them when planning to develop new Nature-inspired Algorithms …
[HTML][HTML] Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods
The evaluation of feature selection methods for text classification with small sample datasets
must consider classification performance, stability, and efficiency. It is, thus, a multiple …
must consider classification performance, stability, and efficiency. It is, thus, a multiple …
Improved binary grey wolf optimizer and its application for feature selection
Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …
Interval dominance-based feature selection for interval-valued ordered data
Dominance-based rough approximation discovers inconsistencies from ordered criteria and
satisfies the requirement of the dominance principle between single-valued domains of …
satisfies the requirement of the dominance principle between single-valued domains of …
A new feature selection method to improve the document clustering using particle swarm optimization algorithm
The large amount of text information on the Internet and in modern applications makes
dealing with this volume of information complicated. The text clustering technique is an …
dealing with this volume of information complicated. The text clustering technique is an …
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Landslides are a manifestation of slope instability causing different kinds of damage
affecting life and property. Therefore, high-performance-based landslide prediction models …
affecting life and property. Therefore, high-performance-based landslide prediction models …
[HTML][HTML] A recent overview of the state-of-the-art elements of text classification
MM Mirończuk, J Protasiewicz - Expert Systems with Applications, 2018 - Elsevier
The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …
classification. For this purpose, we first select and investigate the primary and recent studies …
Chaotic vortex search algorithm: metaheuristic algorithm for feature selection
Abstract The Vortex Search Algorithm (VSA) is a meta-heuristic algorithm that has been
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
A survey on semi-supervised feature selection methods
Feature selection is a significant task in data mining and machine learning applications
which eliminates irrelevant and redundant features and improves learning performance. In …
which eliminates irrelevant and redundant features and improves learning performance. In …