Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization

Evolutionary competitive swarm exploring optimal support vector machines and feature weighting

(2021) Ala’ M. Al-Zoubi et al.   Soft Computing

SMOTE-NaN-DE: Addressing the noisy and borderline examples problem in imbalanced classification by natural neighbors and differential evolution

(2021) Junnan Li et al.   KNOWLEDGE-BASED SYSTEMS

Evolving data-adaptive support vector machines for binary classification

(2021) Wojciech Dudzik et al.   KNOWLEDGE-BASED SYSTEMS

A subregion division based multi-objective evolutionary algorithm for SVM training set selection

(2020) Fan Cheng et al.   NEUROCOMPUTING

Density-weighted support vector machines for binary class imbalance learning

(2020) Barenya Bikash Hazarika et al.   NEURAL COMPUTING & APPLICATIONS

Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges

(2020) Aritz D. Martinez et al.   Information Fusion

EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification

(2020) Hoang Lam Le et al.   APPLIED SOFT COMPUTING

Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules of Nonlinear Decision Trees for Classification Problems

(2020) Yashesh Dhebar et al.   IEEE Transactions on Cybernetics

Cost-sensitive support vector machines

(2019) Arya Iranmehr et al.   NEUROCOMPUTING

The impact of class imbalance in classification performance metrics based on the binary confusion matrix

(2019) Amalia Luque et al.   PATTERN RECOGNITION

Selecting training sets for support vector machines: a review

(2018) Jakub Nalepa et al.   ARTIFICIAL INTELLIGENCE REVIEW

MC2ESVM: Multiclass Classification Based on Cooperative Evolution of Support Vector Machines

(2018) Alejandro Rosales-Perez et al.   IEEE Computational Intelligence Magazine

A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications

(2018) Ankur Sinha et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

(2018) Alberto Fernandez et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

A multi-objective evolutionary approach to training set selection for support vector machine

(2018) Giovanni Acampora et al.   KNOWLEDGE-BASED SYSTEMS

A Cost-Sensitive Deep Belief Network for Imbalanced Classification

(2018) Chong Zhang et al.   IEEE Transactions on Neural Networks and Learning Systems

Multiobjective Support Vector Machines: Handling Class Imbalance With Pareto Optimality

(2018) Shounak Datta et al.   IEEE Transactions on Neural Networks and Learning Systems

Geometric Structural Ensemble Learning for Imbalanced Problems

(2018) Zonghai Zhu et al.   IEEE Transactions on Cybernetics

An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles

(2017) Alejandro Rosales-Perez et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Statistical comparison of classifiers through Bayesian hierarchical modelling

(2017) Giorgio Corani et al.   MACHINE LEARNING

Classification of Imbalanced Data by Oversampling in Kernel Space of Support Vector Machines

(2017) Josey Mathew et al.   IEEE Transactions on Neural Networks and Learning Systems

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification

(2017) Qi Kang et al.   IEEE Transactions on Cybernetics

Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs

(2015) Shounak Datta et al.   NEURAL NETWORKS

Surrogate-assisted multi-objective model selection for support vector machines

(2015) Alejandro Rosales-Pérez et al.   NEUROCOMPUTING

Multi-objective model type selection

(2014) Alejandro Rosales-Pérez et al.   NEUROCOMPUTING

Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics

(2011) Victoria López et al.   EXPERT SYSTEMS WITH APPLICATIONS

Tuning SVM parameters by using a hybrid CLPSO–BFGS algorithm

(2010) Shutao Li et al.   NEUROCOMPUTING

Some Properties of Gaussian Reproducing Kernel Hilbert Spaces and Their Implications for Function Approximation and Learning Theory

(2009) Ha Quang Minh   CONSTRUCTIVE APPROXIMATION

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING