Classification of textile fabrics using statistical multivariate techniques
C. Kiruthika and
R. Chandrasekaran
Journal of Applied Statistics, 2012, vol. 39, issue 5, 1129-1138
Abstract:
In this study, an attempt has been made to classify the textile fabrics based on the physical properties using statistical multivariate techniques like discriminant analysis and cluster analysis. Initially, the discriminant functions have been constructed for the classification of the three known categories of fabrics made up of polyster, lyocell/viscose and treated-polyster. The classification yielded hundred per cent accuracy. Each of the three different categories of fabrics has been further subjected to the K-means clustering algorithm that yielded three clusters. These clusters are subjected to discriminant analysis which again yielded a 100% correct classification, indicating that the clusters are well separated. The properties of clusters are also investigated with respect to the measurements.
Date: 2012
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2011.644521 (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:taf:japsta:v:39:y:2012:i:5:p:1129-1138
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/02664763.2011.644521
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().