C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Information Processing and Management: an International Journal
Machine Learning
Prediction games and arcing algorithms
Neural Computation
Automatic classification using supervised learning in a medical document filtering application
Information Processing and Management: an International Journal
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Machine Learning
Credit Scoring and Its Applications
Credit Scoring and Its Applications
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Learning Bayesian network classifiers by maximizing conditional likelihood
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Neural network ensemble strategies for financial decision applications
Computers and Operations Research
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
On diversity and accuracy of homogeneous and heterogeneous ensembles
International Journal of Hybrid Intelligent Systems
Neural nets versus conventional techniques in credit scoring in Egyptian banking
Expert Systems with Applications: An International Journal
A practical approach to credit scoring
Expert Systems with Applications: An International Journal
A Hybrid Credit Scoring Model Based on Genetic Programming and Support Vector Machines
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 07
A systematic analysis of performance measures for classification tasks
Information Processing and Management: an International Journal
Data classification process for security and privacy based on a fuzzy logic classifier
International Journal of Electronic Finance
Computational Statistics & Data Analysis
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Construction of classification models for credit policies in banks
International Journal of Electronic Finance
Open-source machine learning: R meets Weka
Computational Statistics - Proceedings of DSC 2007
A comparative assessment of ensemble learning for credit scoring
Expert Systems with Applications: An International Journal
Credit crunch and loan acquisition concerns in a recessional economy: an empirical study
International Journal of Electronic Finance
Combining integrated sampling with SVM ensembles for learning from imbalanced datasets
Information Processing and Management: an International Journal
Risk indicators of e-credit assessment system
International Journal of Electronic Finance
Integrating geolocation into electronic finance applications for additional security
International Journal of Electronic Finance
International Journal of Intelligent Systems in Accounting and Finance Management
Measuring e-statement quality impact on customer satisfaction and loyalty
International Journal of Electronic Finance
Towards e-banking: the evolution of business models in financial services
International Journal of Electronic Finance
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Two-level classifier ensembles for credit risk assessment
Expert Systems with Applications: An International Journal
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
Potential indicators for stock index prediction: a perspective
International Journal of Electronic Finance
A multidimensional analysis of data quality for credit risk management: New insights and challenges
Information and Management
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Credit risk assessment is acting as a survival weapon in almost every financial institution. It involves deep and sensitive analysis of various financial, social, demographic and other pertinent data provided by the customers and about the customers for building a more accurate and robust electronic finance system. The classification problem is one of the major concerned in the process of analysing gamut of data; however, its complexity has ignited us to use machine learning-based approaches. In this paper, some machine learning algorithms have been studied and compared their effectiveness for credit risk assessment. Further, as an extension of our study, we develop a novel sliding window-based meta-majority voting ensemble learning to improve the prediction accuracy of credit risk assessment problem by properly analysing the underlying samples. The experimental findings draw a clear line between the proposed ensembler and traditional ensemblers. Moreover, the proposed method is very promising vis-à-vis of individual classifiers.