Extended Kernel Subsets Analysis for Qualitative Model Learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we continue our previous research on kernel subset analysis for Qualitative Model Learning (QML).We focus on investigating the kernel subsets and learning precision
of QML when the number of the training data is relatively large, which makes the corresponding kernel subset experiments very computationally expensive to perform. We use a twocompartment
model with two qualitatively different inputs as our testbed to exhaustively perform the kernel subset experiments by the GENMODEL algorithm. An analysis on the obtained
experimental results indicates that there exist patterns in the formation of kernel subsets, and the solution space analysis further reveals the distribution of kernel subsets in the solution
space.
Original languageEnglish
Title of host publicationProceeding of the 12th UK Workshop on Computational Intelligence
EditorsP. De Wilde, G.M. Coghill, A.V. Kononova
Place of PublicationEdinburgh, UK
PublisherIEEE Explore
Pages1-7
Number of pages7
ISBN (Electronic)978-1-4673-4392-3
DOIs
Publication statusPublished - 2012
EventComputational Intelligence (UKCI), 2012 12th UK Workshop on - , United Kingdom
Duration: 5 Sep 20127 Sep 2012

Conference

ConferenceComputational Intelligence (UKCI), 2012 12th UK Workshop on
CountryUnited Kingdom
Period5/09/127/09/12

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  • Cite this

    Pang, W., & Coghill, G. M. (2012). Extended Kernel Subsets Analysis for Qualitative Model Learning. In P. De Wilde, G. M. Coghill, & A. V. Kononova (Eds.), Proceeding of the 12th UK Workshop on Computational Intelligence (pp. 1-7). IEEE Explore. https://doi.org/10.1109/UKCI.2012.6335774