Knowledge discovery from noisy imbalanced and incomplete binary class data

Radial-Based oversampling for noisy imbalanced data classification

(2019) Michał Koziarski et al.   NEUROCOMPUTING

Evolutionary inversion of class distribution in overlapping areas for multi-class imbalanced learning

(2019) Everlandio R.Q. Fernandes et al.   INFORMATION SCIENCES

An overlap-sensitive margin classifier for imbalanced and overlapping data

(2018) Han Kyu Lee et al.   EXPERT SYSTEMS WITH APPLICATIONS

Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE

(2018) Georgios Douzas et al.   INFORMATION SCIENCES

A class center based approach for missing value imputation

(2018) Chih-Fong Tsai et al.   KNOWLEDGE-BASED SYSTEMS

Fuzzy rule-based oversampling technique for imbalanced and incomplete data learning

(2018) Gencheng Liu et al.   KNOWLEDGE-BASED SYSTEMS

A study on combining dynamic selection and data preprocessing for imbalance learning

(2018) Anandarup Roy et al.   NEUROCOMPUTING

Under-sampling class imbalanced datasets by combining clustering analysis and instance selection

(2018) Chih-Fong Tsai et al.   INFORMATION SCIENCES

Fuzzy-Based Information Decomposition for Incomplete and Imbalanced Data Learning

(2017) Shigang Liu et al.   IEEE TRANSACTIONS ON FUZZY SYSTEMS

Noise Reduction A Priori Synthetic Over-Sampling for class imbalanced data sets

(2017) William A. Rivera   INFORMATION SCIENCES

Clustering-based undersampling in class-imbalanced data

(2017) Wei-Chao Lin et al.   INFORMATION SCIENCES

PSO-based method for SVM classification on skewed data sets

(2017) Jair Cervantes et al.   NEUROCOMPUTING

Synthetic minority oversampling technique for multiclass imbalance problems

(2017) Tuanfei Zhu et al.   PATTERN RECOGNITION

Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants

(2017) Max Schubach et al.   Scientific Reports

A Novel Algorithm for Imbalance Data Classification Based on Genetic Algorithm Improved SMOTE

(2016) Kun Jiang et al.   ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING

Feature projection k-NN classifier model for imbalanced and incomplete medical data

(2016) Piotr Porwik et al.   Biocybernetics and Biomedical Engineering

Geometric mean based boosting algorithm with over-sampling to resolve data imbalance problem for bankruptcy prediction

(2015) Myoung-Jong Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

(2015) José A. Sáez et al.   INFORMATION SCIENCES

A hybrid approach to integrate fuzzy C-means based imputation method with genetic algorithm for missing traffic volume data estimation

(2015) Jinjun Tang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Learned lessons in credit card fraud detection from a practitioner perspective

(2014) Andrea Dal Pozzolo et al.   EXPERT SYSTEMS WITH APPLICATIONS

SYNTHETIC OVERSAMPLING OF INSTANCES USING CLUSTERING

(2013) ATLÁNTIDA I. SÁNCHEZ et al.   International Journal on Artificial Intelligence Tools

Performance of corporate bankruptcy prediction models on imbalanced dataset: The effect of sampling methods

(2013) Ligang Zhou   KNOWLEDGE-BASED SYSTEMS

A Novel Boundary Oversampling Algorithm Based on Neighborhood Rough Set Model: NRSBoundary-SMOTE

(2013) Feng Hu et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Effective detection of sophisticated online banking fraud on extremely imbalanced data

(2012) Wei Wei et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique

(2011) Chumphol Bunkhumpornpat et al.   APPLIED INTELLIGENCE

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

An empirical study of the classification performance of learners on imbalanced and noisy software quality data

(2011) Chris Seiffert et al.   INFORMATION SCIENCES

Multiple imputation by chained equations: what is it and how does it work?

(2011) Melissa J. Azur et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes

(2011) Mikel Galar et al.   PATTERN RECOGNITION

A robust missing value imputation method for noisy data

(2010) Bing Zhu et al.   APPLIED INTELLIGENCE

A comprehensive empirical evaluation of missing value imputation in noisy software measurement data

(2007) Jason Van Hulse et al.   JOURNAL OF SYSTEMS AND SOFTWARE