Multi-class financial distress prediction based on support vector machines integrated with the decomposition and fusion methods

Financial distress prediction: Regularized sparse-based Random Subspace with ER aggregation rule incorporating textual disclosures

(2020) Gang Wang et al.   APPLIED SOFT COMPUTING

A novel purity-based k nearest neighbors imputation method and its application in financial distress prediction

(2019) Ching-Hsue Cheng et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A new perspective of performance comparison among machine learning algorithms for financial distress prediction

(2019) Yu-Pei Huang et al.   APPLIED SOFT COMPUTING

Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting

(2019) Jie Sun et al.   Information Fusion

A dynamic financial distress forecast model with multiple forecast results under unbalanced data environment

(2019) Feng Shen et al.   KNOWLEDGE-BASED SYSTEMS

An investigation of bankruptcy prediction in imbalanced datasets

(2018) David Veganzones et al.   DECISION SUPPORT SYSTEMS

A new random subspace method incorporating sentiment and textual information for financial distress prediction

(2018) Gang Wang et al.   Electronic Commerce Research and 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

One versus one multi-class classification fusion using optimizing decision directed acyclic graph for predicting listing status of companies

(2017) Ligang Zhou et al.   Information Fusion

Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble

(2017) Jie Sun et al.   KNOWLEDGE-BASED SYSTEMS

A nonlinear subspace multiple kernel learning for financial distress prediction of Chinese listed companies

(2016) Xiangrong Zhang et al.   NEUROCOMPUTING

Predicting profitability of listed construction companies based on principal component analysis and support vector machine—Evidence from China

(2015) Hong Zhang et al.   AUTOMATION IN CONSTRUCTION

Prediction of financial distress: An empirical study of listed Chinese companies using data mining

(2015) Ruibin Geng et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

A comparison on multi-class classification methods based on least squares twin support vector machine

(2015) Divya Tomar et al.   KNOWLEDGE-BASED SYSTEMS

Novel feature selection methods to financial distress prediction

(2013) Fengyi Lin et al.   EXPERT SYSTEMS WITH APPLICATIONS

Imbalance-oriented SVM methods for financial distress prediction: a comparative study among the new SB-SVM-ensemble method and traditional methods

(2013) Jie Sun et al.   JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

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

(2013) Ligang Zhou   KNOWLEDGE-BASED SYSTEMS

Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches

(2013) Jie Sun et al.   KNOWLEDGE-BASED SYSTEMS

Concept Drift-Oriented Adaptive and Dynamic Support Vector Machine Ensemble With Time Window in Corporate Financial Risk Prediction

(2013) Jie Sun et al.   IEEE Transactions on Systems Man Cybernetics-Systems

Partial Least Square Discriminant Analysis for bankruptcy prediction

(2012) Carlos Serrano-Cinca et al.   DECISION SUPPORT SYSTEMS

Predicting financial distress of the South Korean manufacturing industries

(2012) Jae Kwon Bae   EXPERT SYSTEMS WITH APPLICATIONS

Enhancing directed binary trees for multi-class classification

(2012) Elena Montañés et al.   INFORMATION SCIENCES

Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence

(2011) F. Mokhatab Rafiei et al.   EXPERT SYSTEMS WITH APPLICATIONS

SFFS-PC-NN optimized by genetic algorithm for dynamic prediction of financial distress with longitudinal data streams

(2011) Jie Sun et al.   KNOWLEDGE-BASED SYSTEMS

The random subspace binary logit (RSBL) model for bankruptcy prediction

(2011) Hui Li et al.   KNOWLEDGE-BASED SYSTEMS

Fuzzy Support Vector Machine for bankruptcy prediction

(2010) Arindam Chaudhuri et al.   APPLIED SOFT COMPUTING

Dynamic financial distress prediction using instance selection for the disposal of concept drift

(2010) Jie Sun et al.   EXPERT SYSTEMS WITH APPLICATIONS

The use of hybrid manifold learning and support vector machines in the prediction of business failure

(2010) Fengyi Lin et al.   KNOWLEDGE-BASED SYSTEMS

Ensemble with neural networks for bankruptcy prediction

(2009) Myoung-Jong Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

A hybrid approach of DEA, rough set and support vector machines for business failure prediction

(2009) Ching-Chiang Yeh et al.   EXPERT SYSTEMS WITH APPLICATIONS

CLASSIFICATION OF IMBALANCED DATA: A REVIEW

(2009) YANMIN SUN et al.   INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE

A cross model study of corporate financial distress prediction in Taiwan: Multiple discriminant analysis, logit, probit and neural networks models

(2009) Tzong-Huei Lin   NEUROCOMPUTING

Listed companies’ financial distress prediction based on weighted majority voting combination of multiple classifiers

(2007) Jie Sun et al.   EXPERT SYSTEMS WITH APPLICATIONS

Data mining method for listed companies’ financial distress prediction

(2006) Jie Sun et al.   KNOWLEDGE-BASED SYSTEMS