Random survival forests for high-dimensional data

Journal article

Peer reviewed

Hemant Ishwaran, Udaya B Kogalur, Xi Chen and Andy J Minn

Statistical analysis and data mining, Vol.4(1), pp.115-132

2011-02

Abstract

minimal depth

variable selection

maximal subtree

forests

trees

VIMP

11 Record Views

Title: Random survival forests for high-dimensional data
Creators: Hemant Ishwaran - Dept of Quantitative Health Sciences JJN3-01, Cleveland Clinic, Cleveland OH 44195
Udaya B Kogalur - Dept of Quantitative Health Sciences JJN3-01, Cleveland Clinic, Cleveland OH 44195
Xi Chen - Dept of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232-6848
Andy J Minn - Dept of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104
Publication Details: Statistical analysis and data mining, Vol.4(1), pp.115-132
Publisher: Wiley Subscription Services, Inc., A Wiley Company
Number of pages: 18
Academic Unit: Miller School of Medicine; UMMG Department of Public Health Sciences Research
Language: English
Resource Type: Journal article
Record Identifier: 991031599164902976