A new deep learning ensemble credit risk evaluation model with an improved synthetic minority oversampling technique

Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction

(2020) Matthew C. Robinson et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

GEV-NN: A deep neural network architecture for class imbalance problem in binary classification

(2020) Lkhagvadorj Munkhdalai et al.   KNOWLEDGE-BASED SYSTEMS

Financial time series forecasting with deep learning : A systematic literature review: 2005–2019

(2020) Omer Berat Sezer et al.   APPLIED SOFT COMPUTING

Statistical and machine learning models in credit scoring: A systematic literature survey

(2020) Xolani Dastile et al.   APPLIED SOFT COMPUTING

An ensemble semi-supervised learning method for predicting defaults in social lending

(2019) Aleum Kim et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Feature construction for fraudulent credit card cash-out detection

(2019) Yue Wu et al.   DECISION SUPPORT SYSTEMS

Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

(2019) Paweł Pławiak et al.   APPLIED SOFT COMPUTING

A combined entropy-based approach for a proactive credit scoring

(2019) Salvatore Carta et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

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

(2018) Lean Yu et al.   APPLIED SOFT COMPUTING

Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

(2018) Ha Young Kim 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

Variable selection and validation in multivariate modelling

(2018) Lin Shi et al.   BIOINFORMATICS

Enterprise credit risk evaluation based on neural network algorithm

(2018) Xiaobing Huang et al.   Cognitive Systems Research

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

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

To Combat Multi-Class Imbalanced Problems by Means of Over-Sampling Techniques

(2016) Lida Abdi et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Cost-sensitive Global Model Trees applied to loan charge-off forecasting

(2015) Marcin Czajkowski et al.   DECISION SUPPORT SYSTEMS

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

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

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

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

RAMOBoost: Ranked Minority Oversampling in Boosting

(2010) Sheng Chen et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS