Learning from Data by Interval Linear Programming

Li Wei

doi:10.4028/www.scientific.net/KEM.439-440.710

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HomeKey Engineering MaterialsKey Engineering Materials Vols. 439-440Learning from Data by Interval Linear Programming

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.

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Periodical:

Key Engineering Materials (Volumes 439-440)

Pages:

710-714

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.439-440.710

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Online since:

June 2010

Authors:

Li Wei

Keywords:

Generalized Inverse of Matrix, Interval Linear Programming, Learning, Regression

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