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Pattern Recognition
ID: 174193
Sergios Theodoridis, Konstantinos Koutroumbas
This book is a classical and unsupervised pattern, a supervised, unsupervised and semi-supervised pattern recognition. The authors, leading experts in the field of pattern recognition, have been provided with the broad spectrum of information. The very latest methods are: semi-supervised learning, combining clustering algorithms, and relevance feedback.
1. Introduction
2. Classifiers based on Bayes Decision
3. Linear Classifiers
4. Nonlinear Classifiers
5. Feature Selection
6. Feature Generation I: Data Transformation and Dimensionality Reduction
7. Feature Generation II
8. Template Matching
9. Context Depedant Clarification
10. Evaultion system
11. Clustering: Basic Concepts
12. Clustering Algorithms: L Sequential Algorithms
13. Clustering Algorithms II: Hierarchical
14. Clustering Algorithms III: Based on Function Optimization
15. Clustering Algorithms IV: Clustering
16. Cluster Validity
174193
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Sergios Theodoridis, Konstantinos Koutroumbas