Proceedings ArticleDOI
Effective rule induction using incremental approach for a dynamic information system
B. K. Tripathy,K Kumaran,M. Sumaithri,T Swathi +3 more
- Vol. 3, pp 308-312
TLDR
This paper proposed a rule induction algorithm, ELEM, which is an enhanced version of one of the existing rule induction algorithms, LEM1 (3), which is made effective by reducing the database scans required to generate the rules.Abstract:
In the present day scenario, there are large volumes of data available in several fields, which we can make use of effectively, for decision making. This can be achieved by inducing rules through various rule induction approaches that are available. In this paper, we proposed a rule induction algorithm, ELEM, which is an enhanced version of one of the existing rule induction algorithms, LEM1 (3). This is made effective by reducing the database scans required to generate the rules. Also, it provides an incremental approach which makes use of ELEM and deals with any kind of data changes in a dynamic information system.read more
References
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Rough sets
TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
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Zdziasław Pawlak,Andrzej Skowron +1 more
TL;DR: The basic concepts of rough set theory are presented and some rough set-based research directions and applications are pointed out, indicating that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences.
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Intelligent Decision Support
TL;DR: The paper presents the system LERS for rule induction, which computes lower and upper approximations of each concept and induces certain rules and possible rules that can be induced from the input data.
Journal ArticleDOI
Rule induction based on an incremental rough set
TL;DR: This paper proposes an incremental rule-extraction algorithm that updates rule sets by partially modifying the original rule sets, which increases the efficiency and is especially useful while extracting rules in a large database.
Journal ArticleDOI
Incremental Induction of Decision Rules from Dominance-based Rough Approximations
TL;DR: An incremental algorithm generating satisfactory decision rules and a rule post-processing technique are presented based on the Apriori algorithm, designed for medical applications which require a careful selection of the set of decision rules representing medical experience.