credit scoring is a classification problem leading to introducing numerous techniques to deal with it such as support vector machines, neural networks and rule-based classifiers. rule bases are the top priority in credit decision making because of their ability to explicitly distinguish between good and bad applicants.in a credit- scoring context, imbalanced data sets frequently occur as the nu...

In our laboratory, we have been developing a rule-based term extraction system in biomedical domain that contains hand-coded terms and domain specific suffixes, thus we construct a complaint and diagnosis extraction system utilizing the term extraction system. Since the rule-based system was constructed according to the annotated newspaper corpus [3], it must be inappropriate to direct applicat...

Classifiers like ANN & SVM are always preferred over other classification model like decision tree due to higher accuracy but lacking explainability and comprehensibility. Rule extraction techniques bridges gap between accuracy and comprehensibility. To evaluate and compare different rule extraction techniques, we require measures for evaluation and categorization. Taxonomy helps us to select a...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

Over the last years, a number of studies on rule extraction from support vector machines (SVMs) have been introduced [1-5]. The research strategy in these projects is similar: to explore and develop algorithms for rule extraction based on the perception (or “view”) of the underlying SVM which is either explicitly or implicitly assumed within the rule extraction technique. In the context of rule...