Variable selection for hedonic model using machine learning approaches: A case study in Onondaga County, NY

Landscape and Urban Planning

Volumn 107, Issue 3, 2012, Pages 293-306

  Yoo, Sanglim ^a   Im , Jungho ^a,b   Wagner, John E ^a  

^a STATE UNIVERSITY OF NEW YORK   (United States)

^b Ulsan National Institute of Science and Technology   (South Korea)

Author keywords

Cubist; Environmental amenities; Hedonic model; Machine learning; Random Forest; Variable selection

Indexed keywords

DECISION TREES; HOUSES; LEARNING SYSTEMS; MACHINE LEARNING; REGRESSION ANALYSIS; SALES;

CUBIST; ENVIRONMENTAL AMENITIES; ENVIRONMENTAL VARIABLES; HEDONIC MODEL; MACHINE LEARNING APPROACHES; ORDINARY LEAST SQUARES; THEORETICAL FOUNDATIONS; VARIABLE SELECTION;

RANDOM FORESTS;

ACCURACY ASSESSMENT; EMPIRICAL ANALYSIS; HEDONIC ANALYSIS; HOUSING MARKET; LEARNING; NEIGHBORHOOD; REGRESSION ANALYSIS; THEORETICAL STUDY;

NEW YORK [UNITED STATES]; ONONDAGA COUNTY; UNITED STATES;

EID: 84864519896     PISSN: 01692046     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.landurbplan.2012.06.009     Document Type: Article

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