A rule-based classifier with accurate and fast rule term induction for continuous attributes

Manal Almutairi; Frederic Stahl; Max Bramer

doi:10.1109/ICMLA.2018.00068

A rule-based classifier with accurate and fast rule term induction for continuous attributes

Manal Almutairi, Frederic Stahl, Max Bramer

University of Reading

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Rule-based classifiers are considered more expressive, human readable and less prone to over-fitting compared with decision trees, especially when there is noise in the data. Furthermore, rule-based classifiers do not suffer from the replicated subtree problem as classifiers induced by top down induction of decision trees (also known as 'Divide and Conquer'). This research explores some recent developments of a family of rulebased classifiers, the Prism family and more particular G-Prism-FB and G-Prism-DB algorithms, in terms of local discretisation methods used to induce rule terms for continuous data. The paper then proposes a new algorithm of the Prism family based on a combination of Gauss Probability Density Distribution (GPDD), InterQuartile Range (IQR) and data transformation methods. This new rule-based algorithm, termed G-Rules-IQR, is evaluated empirically and outperforms other members of the Prism family in execution time, accuracy and tentative accuracy.

Original language	English
Title of host publication	Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018
Editors	M. Arif Wani, Moamar Sayed-Mouchaweh, Edwin Lughofer, Joao Gama, Mehmed Kantardzic
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	413-420
Number of pages	8
ISBN (Electronic)	978-1-5386-6805-4
ISBN (Print)	978-1-5386-6806-1
DOIs	https://doi.org/10.1109/ICMLA.2018.00068
Publication status	Published - 17 Jan 2019
Event	17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018 - Orlando, United States Duration: 17 Dec 2018 → 20 Dec 2018

Conference

Conference	17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018
Country/Territory	United States
City	Orlando
Period	17/12/18 → 20/12/18

Keywords

Dynamic Rule Term Boundaries
Interquartile Range Rule Term Boundaries
Modular Classification Rule Induction

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10.1109/ICMLA.2018.00068

ICMLA2018
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Accepted author manuscript (Post-print), 520 KB

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Almutairi, M., Stahl, F., & Bramer, M. (2019). A rule-based classifier with accurate and fast rule term induction for continuous attributes. In M. A. Wani, M. Sayed-Mouchaweh, E. Lughofer, J. Gama, & M. Kantardzic (Eds.), Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018 (pp. 413-420). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMLA.2018.00068

Almutairi, Manal ; Stahl, Frederic ; Bramer, Max. / A rule-based classifier with accurate and fast rule term induction for continuous attributes. Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018. editor / M. Arif Wani ; Moamar Sayed-Mouchaweh ; Edwin Lughofer ; Joao Gama ; Mehmed Kantardzic. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 413-420

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Almutairi, M, Stahl, F & Bramer, M 2019, A rule-based classifier with accurate and fast rule term induction for continuous attributes. in MA Wani, M Sayed-Mouchaweh, E Lughofer, J Gama & M Kantardzic (eds), Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018. Institute of Electrical and Electronics Engineers Inc., pp. 413-420, 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, Orlando, United States, 17/12/18. https://doi.org/10.1109/ICMLA.2018.00068

A rule-based classifier with accurate and fast rule term induction for continuous attributes. / Almutairi, Manal; Stahl, Frederic; Bramer, Max.
Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018. ed. / M. Arif Wani; Moamar Sayed-Mouchaweh; Edwin Lughofer; Joao Gama; Mehmed Kantardzic. Institute of Electrical and Electronics Engineers Inc., 2019. p. 413-420.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Almutairi M, Stahl F, Bramer M. A rule-based classifier with accurate and fast rule term induction for continuous attributes. In Wani MA, Sayed-Mouchaweh M, Lughofer E, Gama J, Kantardzic M, editors, Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 413-420 doi: 10.1109/ICMLA.2018.00068

A rule-based classifier with accurate and fast rule term induction for continuous attributes

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Keywords

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