Class Imbalance Ensemble Learning Based on the Margin Theory

Using sub-sampling and ensemble clustering techniques to improve performance of imbalanced classification

(2018) Samad Nejatian et al.   NEUROCOMPUTING

Kernel based online learning for imbalance multiclass classification

(2018) Shuya Ding et al.   NEUROCOMPUTING

Weight-Based Rotation Forest for Hyperspectral Image Classification

(2017) Wei Feng et al.   IEEE Geoscience and Remote Sensing Letters

Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets

(2016) José A. Sáez et al.   PATTERN RECOGNITION

Self-training in significance space of support vectors for imbalanced biomedical event data

(2015) Tsendsuren Munkhdalai et al.   BMC BIOINFORMATICS

Imbalanced Hyperspectral Image Classification Based on Maximum Margin

(2015) Tao Sun et al.   IEEE Geoscience and Remote Sensing Letters

Diversity techniques improve the performance of the best imbalance learning ensembles

(2015) José F. Díez-Pastor et al.   INFORMATION SCIENCES

Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem

(2015) Michael J. Siers et al.   INFORMATION SYSTEMS

Exploring issues of training data imbalance and mislabelling on random forest performance for large area land cover classification using the ensemble margin

(2015) Andrew Mellor et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Random Balance: Ensembles of variable priors classifiers for imbalanced data

(2015) José F. Díez-Pastor et al.   KNOWLEDGE-BASED SYSTEMS

Neighbourhood sampling in bagging for imbalanced data

(2015) Jerzy Błaszczyński et al.   NEUROCOMPUTING

Coupling different methods for overcoming the class imbalance problem

(2015) Loris Nanni et al.   NEUROCOMPUTING

Exploiting diversity for optimizing margin distribution in ensemble learning

(2014) Qinghua Hu et al.   KNOWLEDGE-BASED SYSTEMS

A resampling ensemble algorithm for classification of imbalance problems

(2014) Yun Qian et al.   NEUROCOMPUTING

Ensembles of $({\alpha})$-Trees for Imbalanced Classification Problems

(2013) Yubin Park et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches

(2013) Alberto Fernández et al.   KNOWLEDGE-BASED SYSTEMS

EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling

(2013) Mikel Galar et al.   PATTERN RECOGNITION

Margin-based ordered aggregation for ensemble pruning

(2013) Li Guo et al.   PATTERN RECOGNITION LETTERS

Handling imbalanced data sets with synthetic boundary data generation using bootstrap re-sampling and AdaBoost techniques

(2013) Putthiporn Thanathamathee et al.   PATTERN RECOGNITION LETTERS

Multiclass Imbalance Problems: Analysis and Potential Solutions

(2012) Shuo Wang et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS

Margin distribution based bagging pruning

(2012) Zongxia Xie et al.   NEUROCOMPUTING

Dynamic classifier ensemble using classification confidence

(2012) Leijun Li et al.   NEUROCOMPUTING

Inverse random under sampling for class imbalance problem and its application to multi-label classification

(2012) Muhammad Atif Tahir et al.   PATTERN RECOGNITION

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

(2011) M. Galar et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE

Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data

(2010) Taghi M. Khoshgoftaar et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

Evolutionary Undersampling for Classification with Imbalanced Datasets: Proposals and Taxonomy

(2009) Salvador García et al.   EVOLUTIONARY COMPUTATION

Learning from Imbalanced Data

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

Class Conditional Nearest Neighbor for Large Margin Instance Selection

(2009) E. Marchiori   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

(2009) Chris Seiffert et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

SPSM: A NEW HYBRID DATA CLUSTERING ALGORITHM FOR NONLINEAR DATA ANALYSIS

(2009) UREERAT WATTANACHON et al.   INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE

Roughly balanced bagging for imbalanced data

(2009) Shohei Hido et al.   Statistical Analysis and Data Mining