Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).

使用matlab从0构建模式识别算法

PatternRecognition - C++, Matlab

pattern recognition practice by matlab

Homework of Pattern Recognition in Matlab

The dataset using photos of many hollywood artist faces