Trait-based risk assessment for invasive species: High performance across diverse taxonomic groups, geographic ranges and machine learning/statistical tools

Diversity and Distributions

Volumn 17, Issue 3, 2011, Pages 451-461

  Keller, Reuben P ^a   Kocev, Dragi ^b   Džeroski, Sašo ^b  

^a UNIVERSITY OF CHICAGO   (United States)

^b JO EF STEFAN INSTITUTE   (Slovenia)

Author keywords

Artificial intelligence; Biological invasions; Logistic regression; Machine learning; Random forests; Receiver operator curve; Traits

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGICAL INVASION; DATA SET; FOREST ECOSYSTEM; HABITAT CONSERVATION; INVASIVE SPECIES; LOGISTICS; PERFORMANCE ASSESSMENT; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICAL ANALYSIS; TAXONOMY;

EID: 79953801162     PISSN: 13669516     EISSN: 14724642     Source Type: Journal    
DOI: 10.1111/j.1472-4642.2011.00748.x     Document Type: Article

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