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1 Introduction
2 CLASSIFIERS BASED ON BAYES DECISION THEORY
3 LINEAR CLASSIFIERS
4 NONLINEAR CLASSIFIERS
5 FEATURE SELECTION
6 FEATURE GENERATION I: LINEAR TRANSFORMS
7 FEATURE GENERATION I1
8 TEMPLATE MATCHING
9 CONTEXT-DEPENDENT CLASSIFICATION
10 SYSTEM EVALUATION
11 CLUSTERING: BASIC CONCEPTS
12 CLUSTERING ALGORITHMS I: SEQUENTIAL ALGORITHMS
13 CLUSTERING ALGORITHMS 11: HIERARCHICAL ALGORITHMS
14 CLUSTERING ALGORITHMS 111: SCHEMES BASED ON FUNCTION OPTIMIZATION
15 CLUSTERING ALGORITHMS IV
16 CLUSTER VALIDITY
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PATTERN RECOGNITION
SECOND EDITION
SERGIOS THEODORIDIS,
KONSTANTINOS KOUTROUMBAS
SECOND EDITION
SERGIOS THEODORIDIS,
KONSTANTINOS KOUTROUMBAS
Table of Contents
2 CLASSIFIERS BASED ON BAYES DECISION THEORY
3 LINEAR CLASSIFIERS
4 NONLINEAR CLASSIFIERS
5 FEATURE SELECTION
6 FEATURE GENERATION I: LINEAR TRANSFORMS
7 FEATURE GENERATION I1
8 TEMPLATE MATCHING
9 CONTEXT-DEPENDENT CLASSIFICATION
10 SYSTEM EVALUATION
11 CLUSTERING: BASIC CONCEPTS
12 CLUSTERING ALGORITHMS I: SEQUENTIAL ALGORITHMS
13 CLUSTERING ALGORITHMS 11: HIERARCHICAL ALGORITHMS
14 CLUSTERING ALGORITHMS 111: SCHEMES BASED ON FUNCTION OPTIMIZATION
15 CLUSTERING ALGORITHMS IV
16 CLUSTER VALIDITY
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Click Here To Download
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