A heuristic approach to classifying labeled/unlabeled data sets

K Y Huang
Additional contact information
K Y Huang: Ling Tung University, Taichung City, Taiwan

Journal of the Operational Research Society, 2012, vol. 63, issue 9, 1248-1257

Abstract: A classification method, which comprises Fuzzy C-Means method, a modified form of the Huang-index function and Variable Precision Rough Set (VPRS) theory, is proposed for classifying labeled/unlabeled data sets in this study. This proposed method, designated as the MVPRS-index method, is used to partition the values of per conditional attribute within the data set and to achieve both the optimal number of clusters and the optimal accuracy of VPRS classification. The validity of the proposed approach is confirmed by comparing the classification results obtained from the MVPRS-index method for UCI data sets and a typical stock market data set with those obtained from the supervised neural networks classification method. Overall, the results show that the MVPRS-index method could be applied to data sets not only with labeled information but also with unlabeled information, and therefore provides a more reliable basis for the extraction of decision-making rules of labeled/unlabeled datasets.

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.palgrave-journals.com/jors/journal/v63/n9/pdf/jors2011103a.pdf Link to full text PDF (application/pdf)
http://www.palgrave-journals.com/jors/journal/v63/n9/full/jors2011103a.html Link to full text HTML (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:63:y:2012:i:9:p:1248-1257

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().