✦ LIBER ✦

A new variable importance measure for random forests with missing data

✍ Scribed by Alexander Hapfelmeier, Torsten Hothorn, Kurt Ulm…

Book ID: 120779337
Publisher: Springer US
Year: 2012
Tongue: English
Weight: 642 KB
Volume: 24
Category: Article
ISSN: 0960-3174
DOI: 10.1007/s11222-012-9349-1

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

An AUC-based permutation variable import

An AUC-based permutation variable importance measure for random forests

✍ Silke Janitza, Carolin Strobl, Anne-Laure Boulesteix 📂 Article 📅 2013 🏛 BioMed Central 🌐 English ⚖ 225 KB

Variable selection by Random Forests usi

Variable selection by Random Forests using data with missing values

✍ Hapfelmeier, A.; Ulm, K. 📂 Article 📅 2014 🏛 Elsevier Science 🌐 English ⚖ 938 KB

Bias in random forest variable importanc

Bias in random forest variable importance measures: Illustrations, sources and a solution

✍ Carolin Strobl; Anne-Laure Boulesteix; Achim Zeileis; Torsten Hothorn 📂 Article 📅 2007 🏛 BioMed Central 🌐 English ⚖ 360 KB

A test of missing completely at random f

A test of missing completely at random for longitudinal data with missing observations

✍ Taesung Park; Seung-Yeoun Lee 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 115 KB 👁 2 views

Liang and Zeger proposed a generalized estimating equations approach to the analysis of longitudinal data. Their models assume that missing observations are missing completely at random in the sense of Rubin. However, when this assumption does not hold, their analysis may yield biased results. In th

A Test of Missing Completely at Random f

A Test of Missing Completely at Random for Multivariate Data with Missing Values

✍ Roderick J. A. Little 📂 Article 📅 1988 🏛 American Statistical Association 🌐 English ⚖ 889 KB

A Random-Effects Model for Multiple Char

A Random-Effects Model for Multiple Characteristics With Possibly Missing Data

✍ Amrik Shah, Nan Laird and David Schoenfeld 📂 Article 📅 1997 🏛 American Statistical Association 🌐 English ⚖ 855 KB