An Analysis on Qualitative Bankruptcy Prediction Rules using Ant-Miner
نویسنده
چکیده
Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using antminer algorithm. Qualitative data are subjective and more difficult to measure. This approach uses qualitative risk factors which include fourteen internal risk factors and sixty eight external risk factors associated with it. By using these factors qualitative prediction rules are generated using ant-miner algorithm and the influence of these factors in bankruptcy is also analyzed. Ant-Miner algorithm is a application of ant colony optimization and data mining concepts. Qualitative rules generated by ant miner algorithm are validated using measure of agreement. These prediction rules yields better accuracy with lesser number of terms than previously applied qualitative bankruptcy prediction methodologies.
منابع مشابه
Framing Qualitative Bankruptcy Prediction Rules Using Ant Colony Algorithm
This paper is to frame qualitative Bankruptcy Prediction (BP) rules using the concept of Ant Colony Algorithm. There are various researches in the area of qualitative BP, among them Genetic Algorithm (GA) seems to more effective. But the redundancy and over lapping of the generated rules cannot be overcome by GA. In our work, we are proposing ACO for generating the rules for qualitative BP. The...
متن کاملData Mining using Advanced Ant Colony Optimization Algorithm and Application to Bankruptcy Prediction
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 ...
متن کاملEffective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm
Bankruptcy is one of the most important issues in Financial Management and investment. Numerous studies on Bankruptcy Prediction have been carried out considering Quantitative factors and they applied different techniques on it to predict Bankruptcy, while only fewer studies have proposed and considered Qualitative factors for prediction of Bankruptcy and even then failure of bankruptcy persist...
متن کاملThe discovery of experts' decision rules from qualitative bankruptcy data using genetic algorithms
Numerous studies on bankruptcy prediction have widely applied data mining techniques to finding out the useful knowledge automatically from financial databases, while few studies have proposed qualitative data mining approaches capable of eliciting and representing experts’ problem-solving knowledge from experts’ qualitative decisions. In an actual risk assessment process, the discovery of bank...
متن کاملImproving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results
Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rule...
متن کامل