Set02: Basic Concepts & Classification Based on Probability

  • feature vector
  • KNN
  • Classification Based on Probability
    • Bayesian classifiers
      • decision boundary
      • Minimum-Risk Classifier
      • Discriminant Function
      • Maximum Likelihood Estimation
      • ML for Gaussian
      • Mixture Models
      • Naïve-Bayes Classifier

        Set03: Classifier Evaluation

        Confusion Matrix
        Two-Class Confusion Matrix
        ROC Curves

        Set04: Linear Classifiers

        MSE Minimum squared error
        Widrow-Hoff Procedure

        Set05: Neural Networks

Set06: Supervised Learning and Generalization

Set07: Radial_Basis Function Networks and Support Vector Machines

Set08: Feature Selection and Dimensionality Reduction