Learning from Data by Interval Linear Programming

Abstract:

Article Preview

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:

Export:

Price:

$35.00

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

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