Paper Title:
Learning from Data by Interval Linear Programming
  Abstract

The linear programming based method are popular methods for learning from empirical data (observations, samples, examples, records). In this paper, an interval linear programming based method for regression problems is proposed. The explicit representation of the general optimal solution of regression problem is obtained in terms of a generalized inverse of the constraint matrix. This explicit solution has obvious theoretical (and possibly computational) advantages over the well-known iterative methods of linear programming.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
710-714
DOI
10.4028/www.scientific.net/KEM.439-440.710
Citation
L. Wei, "Learning from Data by Interval Linear Programming", Key Engineering Materials, Vols. 439-440, pp. 710-714, 2010
Online since
June 2010
Authors
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Price
$32.00
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