Marine Geospatial Ecology Lab

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Blog

Discover the latest research from MGEL Read about the latest research and updates from the Marine Geospatial Ecology Lab

Education

Courses Aliquet adipiscing in dignissim scelerisque fermentum nibh condimentum ligula eget nunc blandit interdum eros, massa ante ipsum senectus quis in. I have been more than 12 years in digital marketing industries, and have help more than 240 companies to grow their business. Featured Courses Sit nunc quis viverra commodo risus integer imperdiet massa blandit …

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Research

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Landing Page

Hi. My name is Ben Arthur. Digital marketing expert. Aliquet adipiscing in dignissim scelerisque fermentum nibh condimentum ligula eget nunc blandit interdum eros, massa ante ipsum senectus quis in. Get My Guide As Featured In: I have been more than 12 years in digital marketing industries, and have help more than 240 companies to grow …

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People

Patrick N. HalpinDirector of the Geospatial Ecology Program Professor of Marine Geospatial Ecology in the Marine Science and Conservation Division of the Nicholas School of the Environment, Duke University  Patrick Halpin is a Professor of Marine Geospatial Ecology and Director of the Geospatial Analysis Program at the Nicholas School of the Environment, Duke University Marine …

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Privacy Policy

Who we are Our website address is: https://mgel.env.duke.edu. © all rights reserved What personal data we collect and why we collect it Comments and Media We do not allow comments or uploads on our site. Site content is created by the Marine Geospatial Lab and associates. Cookies The site does not offer accounts to general …

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User Publications and Reports

This page lists publications and reports for studies and projects that we are aware used MGET in some way. If you know of something that is not listed here, please contact Forthcoming Lins L, Guilini K, Veit-Köhler G, Hauquier F, Alves RMS, Esteves AM, Vanreusel A (in press) The link between meiofauna and surface productivity …

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Random Forest Tools

As part of our recent overhaul of the predictive modeling tools, we added support for random forests as a new modeling type. Random forest (Breiman, 2001) is machine learning algorithm that fits many classification or regression tree (CART) models to random subsets of the input data and uses the combined result (the forest) for prediction. A …

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MGET Publications

If you use MGET in your project, please cite our papers in your publications. Your citations help us continue to provide MGET as free software. Thanks for your support! If you are unable to download any of the papers below, e.g. because they are blocked by a paywall that you cannot get through, please email …

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