Linear Cost-sensitive Max-margin Embedded Feature Selection for SVM

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone

(2020) Davide Chicco et al.   BMC Medical Informatics and Decision Making

Automatic feature scaling and selection for support vector machine classification with functional data

(2020) Asunción Jiménez-Cordero et al.   APPLIED INTELLIGENCE

A mixed integer linear programming support vector machine for cost-effective feature selection

(2020) In Gyu Lee et al.   KNOWLEDGE-BASED SYSTEMS

Simultaneous Feature Selection and Heterogeneity Control for SVM Classification: An Application to Mental Workload Assessment

(2019) Sebastián Maldonado et al.   EXPERT SYSTEMS WITH APPLICATIONS

Dealing with high-dimensional class-imbalanced datasets: Embedded feature selection for SVM classification

(2018) Sebastián Maldonado et al.   APPLIED SOFT COMPUTING

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading

(2018) Shahnorbanun Sahran et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Cost-sensitive Feature Selection for Support Vector Machines

(2018) S. Benítez-Peña et al.   COMPUTERS & OPERATIONS RESEARCH

Cost-Sensitive Feature Selection by Optimizing F-Measures

(2018) Meng Liu et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Double regularization methods for robust feature selection and SVM classification via DC programming

(2018) Julio López et al.   INFORMATION SCIENCES

Sparse Lq -norm least squares support vector machine with feature selection

(2018) Yuan-Hai Shao et al.   PATTERN RECOGNITION

Mixed integer linear programming for feature selection in support vector machine

(2018) Martine Labbé et al.   DISCRETE APPLIED MATHEMATICS

Cost-sensitive feature selection via the ℓ2,1-norm

(2018) Hong Zhao et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Max-Margin feature selection

(2017) Yamuna Prasad et al.   PATTERN RECOGNITION LETTERS

Machine Learning With Big Data: Challenges and Approaches

(2017) Alexandra L'Heureux et al.   IEEE Access

Efficient approaches for ℓ 2-ℓ 0 regularization and applications to feature selection in SVM

(2016) Hoai An Le Thi et al.   APPLIED INTELLIGENCE

Embedded heterogeneous feature selection for conjoint analysis: A SVM approach using L1 penalty

(2016) Sebastián Maldonado et al.   APPLIED INTELLIGENCE

Beyond accuracy: Learning selective Bayesian classifiers with minimal test cost

(2016) Ganggang Kong et al.   PATTERN RECOGNITION LETTERS

Feature Selection Based on the SVM Weight Vector for Classification of Dementia

(2015) Esther E. Bron et al.   IEEE Journal of Biomedical and Health Informatics

Feature selection for Support Vector Machines via Mixed Integer Linear Programming

(2014) Sebastián Maldonado et al.   INFORMATION SCIENCES

A framework for cost-based feature selection

(2014) V. Bolón-Canedo et al.   PATTERN RECOGNITION

An Interior Point Method forL1/2-SVM and Application to Feature Selection in Classification

(2014) Lan Yao et al.   Journal of Applied Mathematics

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

Quantitative Structure–Activity Relationship Models for Ready Biodegradability of Chemicals

(2013) Kamel Mansouri et al.   Journal of Chemical Information and Modeling

Test-cost-sensitive attribute reduction

(2011) Fan Min et al.   INFORMATION SCIENCES

Simultaneous feature selection and classification using kernel-penalized support vector machines

(2010) Sebastián Maldonado et al.   INFORMATION SCIENCES

Optimal feature selection for support vector machines

(2009) Minh Hoai Nguyen et al.   PATTERN RECOGNITION