Section 4.14.1.0 - Basic Writeup - Wikipedia - Generative Model

Section 4.14.1.1 - Hidden Markov model as a HMM Sequence Classifier

Section 4.14.1.2 - Probabilistic context-free grammar as a Classifier

Section 4.14.1.3 - Averaged one-dependence estimators (AODE)

Section 4.14.1.4 - Labelled Latent Dirichlet allocation

Section 4.14.1.5 - Multi-Grain LDA

Section 4.14.1.6 - Restricted Boltzmann machine for Classification

Section 4.14.1.7 - Linear classifiers

Section 4.14.1.8 - Mixture Models

Section 4.14.2.0 - Basic Writeup - Wikipedia - Discriminative Model

Section 4.14.2.1 - Linear classifiers

Section 4.14.2.2 - Quadratic classifiers

Section 4.14.2.3 - Kernel estimation

Section 4.14.2.4 - Boosting Ensemble (meta-algorithm - See Sction 10.5)

Section 4.14.2.5 - Conditional Random Fields (See Section 4.3.4.1)

Section 4.14.2.6 - Decision trees (See Section 4.7)

Section 4.14.2.7 - Random forests (Ensemble - See Section 4.7.8)

Section 4.14.2.8 - Neural networks (See Section 4.2 on ANN's)

Section 4.14.2.9 - Learning vector quantization (See Section 4.2.1.10.1 in Feed Forward Networks)