Paper Title:
A Comparison of Different Methods for LAD Regression
  Abstract

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, X. L. Liu, L. H. Liu, "A Comparison of Different Methods for LAD Regression", Advanced Materials Research, Vols. 143-144, pp. 1328-1331, 2011
Online since
October 2010
Export
Price
$32.00
Share

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

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

Authors: Li Yang, Zhi Gang Jiao, Hui Biao Lin
Chapter 1: CAD/CAM
Abstract:The conventional method of PLC program design is difficult to analysis and solve the complicated control system. Based on examples, the model...
264
  | Authors: Zhong Cheng Zhang
Chapter 1: Computer Science and Theory, Related Studies
Abstract:Leaves have the various shapes, but there was no excellent method to estimate the actual weight of the leaves of a tree until now. Based on...
88
Authors: Sunarin Chanta, Ornurai Sangsawang
III: Urban Planning and Transportation
Abstract:In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to...
578