Back to Results
First PageMeta Content
Regression analysis / Machine learning / Sudden oak death / Species distribution / Cross-validation / Logistic regression / Statistics / Statistical classification / Support vector machine


Ecological Modelling[removed]–90 Support vector machines for predicting distribution of Sudden Oak Death in California Qinghua Guoa,∗ , Maggi Kellya,1 , Catherine H. Grahamb,c a
Add to Reading List

Document Date: 2010-12-20 17:16:44

Open Document

File Size: 670,20 KB

Share Result on Facebook

City

Viburnum / /

Company

Elsevier B.V. / Numerical Terradynamic Simulation Group / /

Country

United States / /

/

Event

Environmental Issue / /

Facility

University of Montana / Hilgard Hall / Valley Life Science Building / Stony Brook University / Life Sciences Building / University of California / Museum of Vertebrate Zoology / /

/

IndustryTerm

natural learning systems / machine learning algorithms / inner product / satellite imagery / artificial neural networks / genetic algorithms / learning algorithms / /

NaturalFeature

California bay / California forests / Sierra Nevada / /

Organization

University of California / Berkeley / University of Montana / Stony Brook University / California GAP / Department of Environmental Science / Policy and Management / School of Forestry / California Oak Mortality Task Force / Department of Ecology and Evolution / /

Person

Maggi Kellya / Catherine H. Grahamb / Trinity / /

/

Position

Carpenter / Corresponding author / /

Product

SVMs / Franklin / /

ProvinceOrState

Mendocino / Calaveras / Mendocino County / El Dorado / Nevada / Mariposa / Amador / Monterey County / New York / Tuolumne / South Dakota / Santa Barbara County / Los Angles / Montana / Madera / San Luis Obispo / Humboldt County / Humboldt / California / Los Angeles County / /

Region

northern California / southern California / central California / /

Technology

radiation / machine learning algorithms / bioinformatics / remote sensing / GPS / machine learning / GIS / /

URL

http /

SocialTag