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20th International Congress on Modelling and Simulation, Adelaide, Australia, 1–6 December 2013 www.mssanz.org.au/modsim2013 Predicting the spatial distribution of seabed gravel content using random forest, spatial int
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Document Date: 2013-11-19 22:01:46

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File Size: 1,48 MB

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City

Canberra / Vienna / Adelaide / L.A. / New York / Girona / /

Company

Andres S.A. / Oxford University Press / Radke L.C. / Hess / CSIRO Publishing / Geoscience Australia / Coastal / /

Country

Australia / Spain / Timor / /

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Event

Product Issues / Environmental Issue / Man-Made Disaster / /

IndustryTerm

data mining / /

MedicalCondition

cancer / /

Movie

A.D. / /

NaturalFeature

Timor Sea / Great Barrier Reef / Joseph Bonaparte Gulf / Seabed Hardness Using Random Forest / Random Forest / /

Organization

International Congress / International Association of Survey Statisticians / Foundation for Statistical Computing / Oxford University / Environmental Geoscience Division / /

Person

Scott Nichol / Riko Hashimoto / Fuqin Li / Vaughn Barrie / Tony Nicholas / Chris Lawson / Zhi Huang / Augusto Sanabria / /

Position

Governor / Survey Statistician / Chief Executive Officer / Pitcher / /

Product

estimates / /

ProvinceOrState

Rhode Island / New York / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / Lecture Notes in Computer Science / /

Region

Northern Australia / /

SportsLeague

International Association / /

Technology

Bioinformatics / DNA Chip / gene expression / data mining / machine learning / Simulation / /

URL

www.mssanz.org.au/modsim2013 / /

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