A review of feature selection methods based on meta-heuristic algorithms

Z Sadeghian, E Akbari, H Nematzadeh… - … of Experimental & …, 2025 - Taylor & Francis
Feature selection is a real-world problem that finds a minimal feature subset from an original
feature set. A good feature selection method, in addition to selecting the most relevant …

A feature selection algorithm of decision tree based on feature weight

HF Zhou, JW Zhang, YQ Zhou, XJ Guo… - Expert Systems with …, 2021 - Elsevier
In order to improve the classification accuracy, a preprocessing step is used to pre-filter
some redundant or irrelevant features before decision tree construction. And a new feature …

A hybrid feature selection method based on information theory and binary butterfly optimization algorithm

Z Sadeghian, E Akbari, H Nematzadeh - Engineering Applications of …, 2021 - Elsevier
Feature selection is the problem of finding the optimal subset of features for predicting class
labels by removing irrelevant or redundant features. S-shaped Binary Butterfly Optimization …

Feature-specific mutual information variation for multi-label feature selection

L Hu, L Gao, Y Li, P Zhang, W Gao - Information Sciences, 2022 - Elsevier
Recent years has witnessed urgent needs for addressing the curse of dimensionality
regarding multi-label data, which attracts wide attention for feature selection. Feature …

A hybrid feature selection approach based on information theory and dynamic butterfly optimization algorithm for data classification

A Tiwari, A Chaturvedi - Expert Systems with Applications, 2022 - Elsevier
The ubiquitous usage of feature selection in search space optimization, information retrieval,
data mining, signal processing, software fault prediction, and bioinformatics is paramount to …

Hybrid particle swarm optimization with spiral-shaped mechanism for feature selection

K Chen, FY Zhou, XF Yuan - Expert Systems with Applications, 2019 - Elsevier
The “curse of dimensionality” is one of the largest problems that influences the quality of the
optimization process in most data mining, pattern recognition, and machine learning tasks …

Feature selection in image analysis: a survey

V Bolon-Canedo, B Remeseiro - Artificial Intelligence Review, 2020 - Springer
Image analysis is a prolific field of research which has been broadly studied in the last
decades, successfully applied to a great number of disciplines. Since the apparition of Big …

Distinguishing two types of labels for multi-label feature selection

P Zhang, G Liu, W Gao - Pattern recognition, 2019 - Elsevier
Multi-label feature selection plays an important role in pattern recognition, which can
improve multi-label classification performance. In traditional multi-label feature selection …

Feature selection with maximal relevance and minimal supervised redundancy

Y Wang, X Li, R Ruiz - IEEE Transactions on Cybernetics, 2022 - ieeexplore.ieee.org
Feature selection (FS) for classification is crucial for large-scale images and bio-microarray
data using machine learning. It is challenging to select informative features from high …

R2CI: Information theoretic-guided feature selection with multiple correlations

J Wan, H Chen, T Li, W Huang, M Li, C Luo - Pattern Recognition, 2022 - Elsevier
Abstract Information theoretic-guided feature selection approaches (ITFSs), which exploit the
uncertainty of information to measure the correlation of features, aim to select the most …