March 2010
Intermediate to advanced
150 pages
7h 13m
English
book
Introduction to Pattern Recognition: A Matlab Approach
by Sergios Theodoridis, Aggelos Pikrakis, Konstantinos Koutroumbas, Dionisis Cavouras
Content preview from Introduction to Pattern Recognition: A Matlab Approach
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CHAPTER
7
Cluste ring
7.1 INTRODUCTION
In previous chapters we dealt with supervised pattern recognition—that is, with problems where the class
label for each training pattern was known. In this chapter we consider the unsupervised case, where
this information is not available. The aim now is to determine “sensible” groups (clusters) formed
by the available patterns in order to extract useful information concerning similarity or dissimilarity
among them.
7.2 BASIC CONCEPTS AND DEFINITIONS
As has been the case so far, we assume that each training pattern is represented by a set of l features that
form an l-dimensional vector x = [x(1),..., x(l)]
T
. Thus, ...
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