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Fuzzy Pattern Recognition

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Fuzzy Pattern RecognitionOverview of Pattern Recognition • Pattern Recognition Procedure Feature Extractio n Feature Reduction Classification (supervised) Clustering (unsupervised or sel ... forganizing) Performanc e Criteria Cluster Validity Class Label Known Unknown Clusters Speech /Image /DataOverview of Pattern Recognition • Supervised Learning for Classification – The class label is known for a set of samples. – Find the decision boundary from the given samples. – For unknown data set, do classification • Unsupervised Learning for Clustering – Set of data is given, find the group or grouping boundary • Reinforcement Learning (Reward/Penalty) – Unkind teacher is given – Trial and Error SchemeOverview of Pattern Recognition • Classification and Clustering Class 1 Class 2 ? Classification Clustering Problem: How to partition How many clusters Problem: Which class to assignFuzzy Pattern RecognitionOverview of Pattern Recognition • Pattern Recognition Algorithm – Based on statistical approach • Parametric Approach – Bay’es Classifier with Gaussian Density – Nonlinear Boundary or Decision Function • Nonparametric Approach for Density Estimation – Parzen window – K-nearest method – Based on Neural Networks • Classifier – Multilayer Perceptron, ART, Neocogntion, … • Clustering – SOM(Self-Organizing Map) [Show More]

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