Masters Theses

Title

Hybrid data mining technique for application in geo-chemical data analysis

Author

Shipra Dutta

Keywords and Phrases

Hybrid Clustering Architecture

Abstract

"The general objective of this research is to investigate the applicability of data mining techniques for knowledge discovery from data that is collected by performing tests to detect and measure hydrocarbons on soil samples collected from different sites. The purpose of the research is to construct a hybrid system using unsupervised learning algorithms and will be used to predict the class of unknown sites with high accuracy. The hybrid system is based on inductive learning trained from a given set of examples. The resulting system is then used to make predictions on previously unseen cases."--Introduction, page 1.

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Fall 2003

Pagination

xii, 85 leaves

Note about bibliography

Includes bibliographical references (leaves 48-50).

Rights

© 2003 Shipra Dutta, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Data mining
Cluster analysis -- Computer programs
Hydrocarbons -- Analysis

Thesis Number

T 8425

Print OCLC #

55215772

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=b5088466~S5

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