Comments on: A random forest guided tour

Giles Hooker () and Lucas Mentch
Additional contact information
Giles Hooker: Cornell University
Lucas Mentch: University of Pittsburgh

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2016, vol. 25, issue 2, No 5, 254-260

Abstract: Abstract We discuss future challenges in developing statistical theory for Random Forests. In particular, we suggest that an analysis of bias and extrapolation is vital to understanding the statistical properties of variable importance measures. We further point to the incorporation of random forests within larger statistical models as an important tool for high-dimensional statistical inference.

Keywords: Random forests; Machine learning; Extrapolation; Variable importance; 62G09 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11749-016-0485-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:testjl:v:25:y:2016:i:2:d:10.1007_s11749-016-0485-3

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11749/PS2

DOI: 10.1007/s11749-016-0485-3

Access Statistics for this article

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Alfonso Gordaliza and Ana F. Militino

More articles in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().