Application of bootstrap to subjective clustering
Keywords and Phrases
Hierarchical clustering; Subjective clustering
"In order to develop successful products in today's competitive market, it is essential to analyze customer needs accurately. Because the number of customer needs collected using a marketing survey tends to be large, it is necessary to group similar needs and identify a small number of representative needs. Subjective Clustering is a statistical method that uses the Hierarchical Clustering algorithm to group similar customer needs into clusters. This research compares Subjective Clustering (SC) and Bootstrap applied to Subjective Clustering (BS-SC) for determining how accurately these methods estimate population primary clusters"--Abstract, leaf iv.
Midha, A. (Ashok)
Mechanical and Aerospace Engineering
M.S. in Mechanical Engineering
University of Missouri--Rolla
Journal article titles appearing in thesis/dissertation
- Comparative study of bootstrap application to subjective clustering
- Investigating the accuracy of subjective clustering and bootstrap application to subjective clustering using an empirical population
x, 48 leaves
© 2006 Nishant Bhardwaj, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5850417~S5
Bhardwaj, Nishant, "Application of bootstrap to subjective clustering" (2006). Masters Theses. 5893.