id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_dodmms5bzrctzhd32bmag6ieti	Fadi Thabtah	Constrained dynamic rule induction learning	2016	21	.pdf	application/pdf	11113	1027	69	is generated, our algorithm updates the candidate items frequency to reflect the discarded data examples Keywords: Classification, Data Mfining, Prediction, PRISM, Rule Induction, Online Security Experimental results using sixteen UCI datasets showed decrement on the number of items per rule. In particular, PRISM algorithm often employs the rule's accuracy as a measure to generate the Having said this, eDRI is a RI algorithm that does not allow items inside rules to share training In other words, 33.33% of the PRISM classifier (2 rules out of six) covers just two data examples. The fact that our algorithm derived less rules by 42.85% than PRISM from a dataset not only minimises the classifier size but also covers larger numbers of training data examples per rule. number of items) derived by PRISM which each classifies few training data examples. of the classifiers generated by PRISM, OneRule, Conjunctive Rule, PART and eDRI algorithms.	./cache/work_dodmms5bzrctzhd32bmag6ieti.pdf	./txt/work_dodmms5bzrctzhd32bmag6ieti.txt