A Comparison of Different Methods for LAD Regression

Abstract:

Article Preview

The least squares method is very sensitive to outliers, one of the simple alternative is the least absolute deviation, i.e. L1 regression, which is less sensitive to outliers, so which is more suitable the small sample and much noise situation. In this paper, the L1 problem of linear model is discussed, the previous work is reviewed systematically, different algorithms is compared, it is proved that the dual forms of different algorithms are the same.

Info:

Periodical:

Advanced Materials Research (Volumes 143-144)

Edited by:

H. Wang, B.J. Zhang, X.Z. Liu, D.Z. Luo, S.B. Zhong

Pages:

1328-1331

DOI:

10.4028/www.scientific.net/AMR.143-144.1328

Citation:

H. J. Chen et al., "A Comparison of Different Methods for LAD Regression", Advanced Materials Research, Vols. 143-144, pp. 1328-1331, 2011

Online since:

October 2010

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.