Performance of random forests and logic regression methods using mini-exome sequence data

Abstract Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regr...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Kim, Yoonhee [verfasserIn]

Li, Qing

Cropp, Cheryl D

Sung, Heejong

Cai, Juanliang

Simpson, Claire L

Perry, Brian

Dasgupta, Abhijit

Malley, James D

Wilson, Alexander F

Bailey-Wilson, Joan E

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2011

Schlagwörter:

Random Forest

Causal Gene

Random Forest Model

Random Forest Method

Random Forest Analysis

Anmerkung:

© Kim et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:

Enthalten in: BMC proceedings - London : BioMed Central, 2007, 5(2011), Suppl 9 vom: 29. Nov.

Übergeordnetes Werk:

volume:5 ; year:2011 ; number:Suppl 9 ; day:29 ; month:11

Links:

Volltext

DOI / URN:

10.1186/1753-6561-5-S9-S104

Katalog-ID:

SPR028445910

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