.png){kind=icon}
返回
Variable selection with error control: another look at stability selection
.png){kind=icon}
OA
AI
DOI：10.1111/j.1467-9868.2011.01034.x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Stability selection was recently introduced by Meinshausen and Buhlmann as a very general technique designed to improve the performance of a variable selection algorithm. It is based on aggregating the results of applying a selection procedure to subsamples of the data. We introduce a variant, called complementary pairs stability selection, and derive bounds both on the expected number of variables included by complementary pairs stability selection that have low selection probability under the original procedure, and on the expected number of high selection probability variables that are excluded. These results require no (e.g. exchangeability) assumptions on the underlying model or on the quality of the original selection procedure. Under reasonable shape restrictions, the bounds can be further tightened, yielding improved error control, and therefore increasing the applicability of the methodology.
Keyword:
Complementary pairs stability selection
r-concavity
Subagging
Subsampling
Variable selection
期刊
J
IF:
3.6
论文数:
1.5K
被引数:
3.2W
机构
引用论文
分享收藏Comparison of discrimination methods for the classification of tumors using gene expression data
OAAI
OAAI分享收藏分享收藏NONPARAMETRIC ESTIMATION OF MULTIVARIATE CONVEX-TRANSFORMED DENSITIES多元凸变换密度的非参数估计.png)
ANNALS OF STATISTICSOAAI
ANNALS OF STATISTICSIF3.7
OAAI分享收藏分享收藏
查看更多内容