Keywords
Cluster analysis, Pattern perception, Unsupervised learning, Hierarchical clustering, Similarity measures (distance metrics), Feature extraction and representation, Cluster validity and evaluation
Abstract
During the past decade and a half, there has been a considerable growth of interest in problems of pattern recognition. Contributions to the growth have been from many of the disciplines including statistics, control theory, operations research, biology, linguistics, and computer science. One of the basic approaches to pattern recognition is cluster analysis, in which various methodologies may be successfully employed. It is the purpose of this research report to investigate some of the basic clustering concepts in automatic pattern recognition.
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
1975
Advisor
Lindenberg, Klaus
Degree
Master of Science (M.S.)
College
College of Engineering
Format
Pages
57 pages
Language
English
Rights
Public Domain
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
Identifier
DP0012690
Subjects
Cluster analysis; Pattern perception; Cluster analysis--Mathematical models; Pattern recognition systems--Statistical methods; Pattern recognition systems--Computer programs; Automatic classification
STARS Citation
DeFilipps, Patricia J., "Clustering Concepts in Automatic Pattern Recognition" (1975). Retrospective Theses and Dissertations. 145.
https://stars.library.ucf.edu/rtd/145
Contributor (Linked data)
University of Central Florida. College of Engineering [VIAF]
Collection (Linked data)
Accessibility Status
Searchable text