Masters Theses

Title

Application of bootstrap to subjective clustering

Keywords and Phrases

Hierarchical clustering; Subjective clustering

Abstract

"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.

Advisor(s)

Takai, Shun

Committee Member(s)

Du, Xiaoping
Midha, A. (Ashok)

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2006

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

Pagination

x, 48 leaves

Note about bibliography

Includes bibliographical references (pages 63-65) and index (pages 66-70).

Rights

© 2006 Nishant Bhardwaj, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Bootstrap (Statistics)
Cluster analysis

Thesis Number

T 9103

Print OCLC #

124068084

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

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