A novel feature selection approach with Pareto optimality for multi-label data

A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

(2020) Laith Abualigah et al.   NEURAL COMPUTING & APPLICATIONS

Distinguishing two types of labels for multi-label feature selection

(2019) Ping Zhang et al.   PATTERN RECOGNITION

A label-specific multi-label feature selection algorithm based on the Pareto dominance concept

(2018) Shima Kashef et al.   PATTERN RECOGNITION

Multi-label feature selection based on neighborhood mutual information

(2016) Yaojin Lin et al.   APPLIED SOFT COMPUTING

A novel attribute reduction approach for multi-label data based on rough set theory

(2016) Hua Li et al.   INFORMATION SCIENCES

Mutual Information-based multi-label feature selection using interaction information

(2015) Jaesung Lee et al.   EXPERT SYSTEMS WITH APPLICATIONS

Memetic feature selection algorithm for multi-label classification

(2015) Jaesung Lee et al.   INFORMATION SCIENCES

Multi-label feature selection based on max-dependency and min-redundancy

(2015) Yaojin Lin et al.   NEUROCOMPUTING

A Review on Multi-Label Learning Algorithms

(2013) Min-Ling Zhang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Mutual information-based feature selection for multilabel classification

(2013) Gauthier Doquire et al.   NEUROCOMPUTING

Feature selection for multi-label classification using multivariate mutual information

(2012) Jaesung Lee et al.   PATTERN RECOGNITION LETTERS

gMLC: a multi-label feature selection framework for graph classification

(2011) Xiangnan Kong et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Multilabel dimensionality reduction via dependence maximization

(2010) Yin Zhang et al.   ACM Transactions on Knowledge Discovery from Data

Feature selection for multi-label naive Bayes classification

(2009) Min-Ling Zhang et al.   INFORMATION SCIENCES