Machine learning for the environment

Principal Investigators:

John M. Drake, and William T. Langford

We believe that environmental science, ecology, and conservation biology would be greatly enriched by expanding the ecologist's analytical toolbox to include machine learning (ML) approaches to data analysis. We use the term ML loosely to distinguish between parametric statistics and a variety of new, computational methods for recognizing and analyzing patterns in data. Generally, parametric methods assume highly restrictive theoretical properties of data, such as additivity, linearity, independence, and distribution (e.g., normality). Ecological... more

Participants and Meetings

Working Group Participants
ActivityDatesFurther Information
Working Group2nd—6th October 2006Participant List  
Working Group2nd—10th June 2007Participant List  
Working Group20th—24th October 2008Participant List  

Participant Contact Information

Jonathan M. Chasejonathan.chase@idiv.deWashington University in St. Louis
Thomas G. Dietterichtgd@eecs.oregonstate.edu
Andrew P. Dobsondobber@princeton.eduPrinceton University
John M. Drakejdrake@uga.eduUniversity of Georgia
Saso Dzeroskisaso.dzeroski@ijs.siUnknown
Jane Elithj.elith@unimelb.edu.auUniversity of Melbourne
Cesare Furlanellofurlan@fbk.euInstituto Trentino Di Cultura
Trevor Hastiehastie@stanford.eduUnknown
Reuben P. Kellerrkeller2@nd.eduUniversity of Notre Dame
William T. Langfordbill.langford@rmit.edu.auRMIT University
Dragos Margineantud.margin@comcast.netUnknown
Julian D. Oldenolden@u.washington.eduUniversity of Washington
Gill Wardgward@stanford.eduStanford University
Matt Whitematt.white@dse.vic.gov.auArthur Rylah Institute for Environmental Research
Bianca Zadroznybianca@ic.uff.brUniversidade Federal Fluminense
Peter M. Bustonbuston@bu.eduConsejo Superior de Investigaciones Científicas (CSIC)
Rich Caruanacaruana@cs.cornell.eduCornell University
T. Jonathan Daviesj.davies@mcgill.caUniversity of California, Santa Barbara
Andreas Krausekrausea@cs.cmu.eduCarnegie Mellon University

Products: Publications, Reports, Datasets, Presentations, Visualizations

TypeProducts of NCEAS Research
Journal Article Buston, Peter M.; Elith, Jane. 2011. Determinants of reproductive success in dominant pairs of clownfish: A boosted regression tree analysis. Journal of Animal Ecology. Vol: 80. Pages 528-538. (Online version)
Journal Article Keller, Reuben P.; Kocev, Dragi; Dzeroski, Saso. 2012. Trait-based risk assessment for invasive species: High performance across diverse taxonomic groups, geographic ranges and machine learning/statistical tools. Diversity and Distributions. Vol: 17(3). Pages 451-461. (Online version)
Journal Article Wilson, Erin E.; Wolkovich, Elizabeth M. 2011. Scavenging: How carnivores and carrion structure communities. Trends in Ecology and Evolution. Vol: 26(3). Pages 129-135. (Online version)
"Machine learning for the environment" is project ID: 10921