ADANOISE: Training neural networks with adaptive noise for imbalanced data classification

Appropriateness of performance indices for imbalanced data classification: An analysis

(2020) Sankha Subhra Mullick et al.   PATTERN RECOGNITION

Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data

(2020) Smaranda Belciug   EXPERT SYSTEMS WITH APPLICATIONS

Champion-challenger analysis for credit card fraud detection: hybrid ensemble and deep learning

(2019) Eunji Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

Direct marketing campaigns in retail banking with the use of deep learning and random forests

(2019) Piotr Ładyżyński et al.   EXPERT SYSTEMS WITH APPLICATIONS

Data imbalance in classification: Experimental evaluation

(2019) Fadi Thabtah et al.   INFORMATION SCIENCES

Imbalanced Deep Learning by Minority Class Incremental Rectification

(2018) Qi Dong et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

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

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

Cross-Validation for Imbalanced Datasets: Avoiding Overoptimistic and Overfitting Approaches [Research Frontier]

(2018) Miriam Seoane Santos et al.   IEEE Computational Intelligence Magazine

Manifold-based synthetic oversampling with manifold conformance estimation

(2017) Colin Bellinger et al.   MACHINE LEARNING

Fast-CBUS: A fast clustering-based undersampling method for addressing the class imbalance problem

(2017) Nir Ofek et al.   NEUROCOMPUTING

A profit-driven Artificial Neural Network (ANN) with applications to fraud detection and direct marketing

(2016) Ashkan Zakaryazad et al.   NEUROCOMPUTING

Learning from Imbalanced Data

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

Forecasting of ozone episode days by cost-sensitive neural network methods

(2009) Che-hui Tsai et al.   SCIENCE OF THE TOTAL ENVIRONMENT