C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
Information Sciences: an International Journal
Incremental Induction of Decision Trees
Machine Learning
Machine Learning
Incremental rules induction based on rule layers
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Incremental rules induction method based on three rule layers
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
Computers in Biology and Medicine
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
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Extending the concepts of rule induction methods based on rough set theory, we introduce a new approach to knowledge acquistion, which induces probabilistic rules in an incremental way, which is called PRIMEROSE-INC (Probabilistic Rule Induction Method based on Rough Sets for Incremental Learning Methods). This method first uses coverage rather than accuracy, to search for the candidates of rules, and secondly uses accuracy to select from the candidates. This system was evaluated on clinical databases on headache and meningitis. The results show that PRIMEROSE-INC induces the same rules as those induced by the former system: PRIMEROSE, which extracts rules from all the datasets, but that the former method requires much computational resources than the latter approach.