C4.5: programs for machine learning
C4.5: programs for machine learning
Forecasting with neural networks
Information and Management
Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
The nature of statistical learning theory
The nature of statistical learning theory
Self organizing neural networks for financial diagnosis
Decision Support Systems
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Hybrid Classifiers for Financial Multicriteria Decision Making: TheCase of Bankruptcy Prediction
Computational Economics
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Neuro-fuzzy approach versus rough-set inspired methodology for intelligent decision support
Information Sciences—Informatics and Computer Science: An International Journal
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Inductive Learning for Risk Classification
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
NeuroRule: A Connectionist Approach to Data Mining
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Classification Rule Discovery with Ant Colony Optimization
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Ant Colony Optimization
Neural and Wavelet Network Models for Financial Distress Classification
Data Mining and Knowledge Discovery
A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
Soft computing system for bank performance prediction
Applied Soft Computing
Expert Systems with Applications: An International Journal
International Journal of Data Analysis Techniques and Strategies
Financial distress prediction by a radial basis function network with logit analysis learning
Computers & Mathematics with Applications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
Classification With Ant Colony Optimization
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
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Ant Colony Optimization ACO is gaining popularity as data mining technique in the domain of Swarm Intelligence for its simple, accurate and comprehensive nature of classification. In this paper the authors propose a novel advanced version of the original ant colony based miner Ant-Miner in order to extract classification rules from data. They call this Advanced ACO-Miner ADACOM. The main goal of ADACOM is to explore the flexibility of using a different knowledge extraction heuristic approach viz. Gini's Index to increase the predictive accuracy and the simplicity of the rules extracted. Further, the authors increase the information and the prediction level of the set of rules extracted by dynamically changing specific parameters. Simulations are performed with ADACOM on a few benchmark datasets Wine, WBC Wisconsin Breast Cancer and Iris from UCI University of California at Irvine data repository and compared with Ant-Miner Parpinelli, Lopes, & Freitas, 2002, Ant-Miner2 Liu, Abbass, & McKay, 2002, Ant-Miner3 Liu, Abbass, & McKay, 2003, Ant-Miner+ Martens, De Backer, Haesen, Vanthienen, Snoeck, & Baesens, 2007 and C4.5 Quinlan, 1993. The results show that ADACOM outperforms the above mentioned algorithms in terms of predictive accuracy, simplicity of rules, sensitivity, specificity and AUC values area under ROC curve. In addition, the ADACOM is also employed to extract rules from bank datasets UK, US, Spanish and Turkish for bankruptcy prediction and the results are compared with that obtained by Ant-Miner. Again ADACOM yielded better results and is proven to be the better choice for solving bankruptcy prediction problems in banks