|
A mixed-integer programming approach to multi-class data classification problem [An article from: European Journal of Operational Research] | ![A mixed-integer programming approach to multi-class data classification problem [An article from: European Journal of Operational Research]](http://ecx.images-amazon.com/images/I/51G4P0G7AGL._SL160_.jpg)
 enlarge | Authors: F. Uney, M. Turkay
Publisher: Elsevier
Category: Book
Buy New: $7.95
Format: Html
Media: Digital
Pages: 10
Publication Date: September 16, 2006
Availability: Available for download now
| |
| Editorial Reviews:
Product Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
This paper presents a new data classification method based on mixed-integer programming. Traditional approaches that are based on partitioning the data sets into two groups perform poorly for multi-class data classification problems. The proposed approach is based on the use of hyper-boxes for defining boundaries of the classes that include all or some of the points in that set. A mixed-integer programming model is developed for representing existence of hyper-boxes and their boundaries. In addition, the relationships among the discrete decisions in the model are represented using propositional logic and then converted to their equivalent integer constraints using Boolean algebra. The proposed approach for multi-class data classification is illustrated on an example problem. The efficiency of the proposed method is tested on the well-known IRIS data set. The computational results on the illustrative example and the IRIS data set show that the proposed method is accurate and efficient on multi-class data classification problems.
|
|
|
| |
