A novel XGBoost extension for credit scoring class-imbalanced data combining a generalized extreme value link and a modified focal loss function

XGBoost Optimized by Adaptive Particle Swarm Optimization for Credit Scoring

(2021) Chao Qin et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

A hybrid sampling algorithm combining M-SMOTE and ENN based on Random forest for medical imbalanced data

(2020) Zhaozhao Xu et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Imbalance-XGBoost: leveraging weighted and focal losses for binary label-imbalanced classification with XGBoost

(2020) Chen Wang et al.   PATTERN RECOGNITION LETTERS

A hybrid data-level ensemble to enable learning from highly imbalanced dataset

(2020) Zhi Chen et al.   INFORMATION SCIENCES

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

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

A random forests quantile classifier for class imbalanced data

(2019) Robert O’Brien et al.   PATTERN RECOGNITION

A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation

(2019) Feng Shen et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data

(2018) Lean Yu et al.   APPLIED SOFT COMPUTING

An experimental comparison of classification techniques in debt recoveries scoring: Evidence from South Africa's unsecured lending market

(2018) Jonah Mushava et al.   EXPERT SYSTEMS WITH APPLICATIONS

A novel ensemble method for credit scoring: Adaption of different imbalance ratios

(2018) Hongliang He et al.   EXPERT SYSTEMS WITH APPLICATIONS

Imbalanced enterprise credit evaluation with DTE-SBD: Decision tree ensemble based on SMOTE and bagging with differentiated sampling rates

(2018) Jie Sun et al.   INFORMATION SCIENCES

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

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

Handling data irregularities in classification: Foundations, trends, and future challenges

(2018) Swagatam Das et al.   PATTERN RECOGNITION

Application of eXtreme gradient boosting trees in the construction of credit risk assessment models for financial institutions

(2018) Yung-Chia Chang et al.   APPLIED SOFT COMPUTING

Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction

(2018) Vicente García et al.   Information Fusion

Learning from class-imbalanced data: Review of methods and applications

(2017) Guo Haixiang et al.   EXPERT SYSTEMS WITH APPLICATIONS

A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring

(2017) Yufei Xia et al.   EXPERT SYSTEMS WITH APPLICATIONS

The study of under- and over-sampling methods’ utility in analysis of highly imbalanced data on osteoporosis

(2017) M. Bach et al.   INFORMATION SCIENCES

Approaches for credit scorecard calibration: An empirical analysis

(2017) Artem Bequé et al.   KNOWLEDGE-BASED SYSTEMS

Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy

(2016) Bartosz Krawczyk et al.   APPLIED SOFT COMPUTING

Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction

(2016) Maciej Zięba et al.   EXPERT SYSTEMS WITH APPLICATIONS

Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model

(2016) Raffaella Calabrese et al.   JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

Dealing with the evaluation of supervised classification algorithms

(2015) Guzman Santafe et al.   ARTIFICIAL INTELLIGENCE REVIEW

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research

(2015) Stefan Lessmann et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

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

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

(2015) Hong Wang et al.   PLoS One

Development and application of consumer credit scoring models using profit-based classification measures

(2014) Thomas Verbraken et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

An insight into the experimental design for credit risk and corporate bankruptcy prediction systems

(2014) Vicente García et al.   JOURNAL OF INTELLIGENT INFORMATION SYSTEMS

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

(2013) Victoria López et al.   INFORMATION SCIENCES

Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

(2013) Raffaella Calabrese et al.   JOURNAL OF APPLIED STATISTICS

A better Beta for the H measure of classification performance

(2013) D.J. Hand et al.   PATTERN RECOGNITION LETTERS

A window of opportunity: Assessing behavioural scoring

(2012) K. Kennedy et al.   EXPERT SYSTEMS WITH APPLICATIONS

An experimental comparison of classification algorithms for imbalanced credit scoring data sets

(2011) Iain Brown et al.   EXPERT SYSTEMS WITH APPLICATIONS

Robust weighted kernel logistic regression in imbalanced and rare events data

(2010) Maher Maalouf et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Multiple classifier architectures and their application to credit risk assessment

(2010) Steven Finlay   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Cost-Sensitive Boosting

(2010) H Masnadi-Shirazi et al.   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

Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

(2009) Salvador García et al.   INFORMATION SCIENCES

Measuring classifier performance: a coherent alternative to the area under the ROC curve

(2009) David J. Hand   MACHINE LEARNING