Masters Theses
Title
Hybrid data mining technique for application in geo-chemical data analysis
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~S5Recommended Citation
Dutta, Shipra, "Hybrid data mining technique for application in geo-chemical data analysis" (2003). Masters Theses. 2439.
http://scholarsmine.mst.edu/masters_theses/2439
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