A working guide to boosted regression trees

Journal of Animal Ecology

Volumn 77, Issue 4, 2008, Pages 802-813

  Elith, J ^a   Leathwick, J R ^b   Hastie, T ^c  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b NATIONAL INSTITUTE OF WATER AND ATMOSPHERIC RESEARCH   (New Zealand)

^c STANFORD UNIVERSITY   (United States)

Author keywords

Data mining; Machine learning; Model averaging; Random forests; Species distributions

Indexed keywords

AUTOMATION; DATA MINING; DATA SET; ECOLOGICAL MODELING; EEL; FRESHWATER ECOSYSTEM; NATIVE SPECIES; NONLINEARITY; POPULATION DISTRIBUTION; REGRESSION ANALYSIS; STATISTICAL ANALYSIS;

ANIMAL; BIOLOGICAL MODEL; DECISION TREE; ECOLOGY; EEL; GROWTH, DEVELOPMENT AND AGING; PHYSIOLOGY; REGRESSION ANALYSIS; REVIEW; STATISTICAL MODEL; STATISTICS;

ANGUILLA; ANIMALS; DECISION TREES; ECOLOGY; MODELS, BIOLOGICAL; MODELS, STATISTICAL; REGRESSION ANALYSIS; STATISTICS AS TOPIC;

AUSTRALASIA; NEW ZEALAND;

ANGUILLA AUSTRALIS;

EID: 44849118698     PISSN: 00218790     EISSN: 13652656     Source Type: Journal    
DOI: 10.1111/j.1365-2656.2008.01390.x     Document Type: Review

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