Abstract
This paper introduces an augmentation hybrid system, referred to as Rated MCRDR. It uses Multiple Classification Ripple Down Rules (MCRDR), a simple and effective knowledge acquisition technique, combined with a neural network.
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References
Dazeley, R., Kang, B.H.: Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR. In: 3rd International Conference on Hybrid Intelligent Systems, IOS Press, Melbourne (2003)
Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, Springer, Heidelberg (1998)
Kang, B.H.: Validating Knowledge Acquisition: Multiple Classification Ripple Down Rules. University of New South Wales, Sydney (1996)
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Dazeley, R., Kang, BH. (2004). An Augmentation Hybrid System for Document Classification and Rating. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_126
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DOI: https://doi.org/10.1007/978-3-540-28633-2_126
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