Exception Included, Ordered Rule Induction from the Set of Exemplars (ExIORISE)
Sayan Sikder1, Sanjeev Kumar Metya2, Rajat Subhra Goswami3
1Sayan Sikder, Department of Computer Science and Engineering, National Institute of Technology, Yupia (Arunachal Pradesh), India.
2Sanjeev Kumar Metya, Department of Electronics and Communication Engineering, National Institute of Technology, Yupia (Arunachal Pradesh), India.
3Rajat Subhra Goswami, Department of Computer Science and Engineering, National Institute of Technology, Yupia (Arunachal Pradesh), India.
Manuscript received on 03 December 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 31 December 2019 | PP: 57-62 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10391292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1039.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An expert system is one which uses collection of data comprising the knowledge to offer guidance or make inferences. Its work in most cases can be seen as classification which is basically the task of assigning objects to different categories or classes, determined by the properties of those objects. Numerous research works have been and being done to develop efficient knowledge acquisition techniques for expert systems. Some state-of-the-art algorithms are great performers but need extensive learning whereas older rule / decision- tree based algorithms perform pretty well with small data sets. Moreover, co-existence of learners of different levels of expertise and accuracy is believed to be encouraged to achieve a cumulative intelligence just like the human beings have. RISE is one such algorithm that infuses both instance-based learning and rule induction. It proved to be quite efficient handling binary and multi-class classification problems for small data sets in terms of accuracy and cost as well. In this work, features like exclusion of inefficient rules, inclusion of exceptions in the rule set and ordering of the rules using weights beforehand are integrated with the classical RISE algorithm to develop a more efficient classifier system named as ExIORISE. Empirical study shows that ExIORISE outperforms RISE, C4.5 and CN2 significantly.
Keywords: Classification, Expert System, Rule / Decision-Tree Based Algorithms, Exceptions; Inefficient Rules, Ordering According To Weight.
Scope of the Article: Expert Systems