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dc.contributor.authorAldridge, Colin Hen_NZ
dc.date.available2011-04-07T03:01:58Z
dc.date.copyright2003-12en_NZ
dc.identifier.citationAldridge, C. H. (2003). Playing possum with knowledge discovery: inducing population density models from spatially referenced ecological data (pp. 119–130). Presented at the 15th Annual Colloquium of the Spatial Information Research Centre (SIRC 2003: Land, Place and Space).en
dc.identifier.urihttp://hdl.handle.net/10523/715
dc.description.abstractThe author’s rough set based knowledge induction methodology (Aldridge 1998) and the C4.5 decision tree algorithm (Quinlan 1993) are applied to spatially referenced ecological data to develop models making use of spatial relationships. The data set records the habitat characteristics and the population distribution of a species of Australian arboreal marsupial, Peteroides volans, commonly known as the greater glider possum. The study area is 1600 hectares of south-eastern Australian coastal ranges and tableland. The ability of the possums to glide between trees suggested that identifying spatial relationships between habitat variables might be important when predicting local population density. A variable-sized “context window” is used in the search for spatial relationships. Other researchers using several machine learning methods to generate both spatial and non-spatial models have already studied the greater glider dataset. The results of these earlier studies are used as benchmarks against which to compare the results of the present work. The models developed using the rough set based algorithms are found to be statistically indistinguishable in terms of classification accuracy from the best of the models reported in the literature.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.urihttp://www.business.otago.ac.nz/SIRC05/conferences/2003/23_Aldridge.pdfen_NZ
dc.subjectrough set theoryen_NZ
dc.subjectC5.0en_NZ
dc.subjectgeographic knowledgeen_NZ
dc.subjectGISen_NZ
dc.subjectData miningen_NZ
dc.subject.lcshQL Zoologyen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titlePlaying possum with knowledge discovery: inducing population density models from spatially referenced ecological dataen_NZ
dc.typeConference or Workshop Item (Paper)en_NZ
dc.description.versionPublisheden_NZ
otago.date.accession2005-11-30en_NZ
otago.relation.pages119-130en_NZ
otago.openaccessOpen
dc.identifier.eprints114en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsSpatial Information Research Centreen_NZ
otago.school.eprintsInformation Scienceen_NZ
dc.description.referencesAldridge, C.H. (1998) A Theory Of Empirical Spatial Knowledge Supporting Rough Set Based Knowledge Discovery in Geographic Databases. Ph.D. Thesis, University of Otago, Dunedin, New Zealand. Brieman, L., Friedman, J.H., Olshen, R.A. and Stone (C.J., 1986) Classification and Regression Trees, Wadsworth International, Belmont, Ca. Fayyad, U.M., Piatetsky-Shapiro, G., and Smyth, P. (1996) The KDD process for extracting useful knowledge from volumes of data. Communications of the ACM, v. 39, no. 11, 27-34. Kennedy, G.J. (1993) A Systematic Approach to the Specification of an Information Systems Development System. PhD Thesis, Department of Information Science, University of Otago, Dunedin, New Zealand. Maddison, R.N. (1983) Information System Methodologies. Pearson, R.A. and McKay, R.I. (1996) Spatial induction for natural resource problems: a case study in wildlife density prediction. Technical Report, School of Computer Science, University College, University of New South Wales. Quinlan, J.R. (1986) Induction of decision tress. Machine Learning 1: 81-86. Quinlan, J.R. (2000) Data Mining Tools See5 and C5.0. http://www.rulequest.com/see5-info.html (23 Nov 2003). Quinlan, J.R (1993) C4.5: Programs For Machine Learning. Morgan Kauffman. Stockwell, D.R.B., Davey, S.M., Davis, J.R., and Noble, I.R. (1990) Using induction trees to predict greater glider density. A I Applications in Natural Re-source Management, v. 4, no. 4, 33-43. Whigham, P.A. (1996) Grammatical Bias for Evolutionary Learning. PhD Thesis, University College, University of New South Wales, Canberra, Australia.en_NZ
otago.event.dates1-2 December 2003en_NZ
otago.event.placeDunedin, New Zealanden_NZ
otago.event.typeconferenceen_NZ
otago.event.title15th Annual Colloquium of the Spatial Information Research Centre (SIRC 2003: Land, Place and Space)en_NZ
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