《pattern recognition》 3rd by Sergios

经典模式识别书 目录： Chapter 1: Introduction Chapter 2: Classifiers Based on Bayes Decision Theory Chapter 3: Linear Classifiers Chapter 4: Nonlinear Classifiers Chapter 5: Feature Selection Chapter 6: Feature Generation I Chapter 7: Feature Generation II Chapter 8: Template Matching Chapter 9: Context-Dependant Classification Chapter 10: System Evaluation Chapter 11: Clustering: Basic Concepts Chapter 12: Clustering Algorithms I (Sequential) Chapter 13: Clustering Algorithms II (Hierarchical) Chapter 14: Clustering Algorithms III (Funct ional Optimization) Chapter 15: Clustering Algorithms IV (Graph Theory) Chapter 16: Cluster Validity ional Optimization) Chapter 15: Clustering Algorithms IV (Graph Theory) Chapter 16: Cluster Validity