Supervised Learning
  Generative
    Sequence
      Markov Process (MDP)
      Hidden Markov Model (HMM)
      Markov Random Fields
    Random
      Naïve Bayes (NB)
      Latent Dirichlet Allocation
      Belief Network
  Discriminative
    Continuous
      Linear Regression
      Logistic Regression
    Discrete
      Neural Networks (ANN)
      Support Vector Machine (SVM)
      Maximum Entropy
      Decision Trees
      Conditional Random Fields (CRF)
      Random Forests
Unsupervised Learning
  Clustering
    K-means Clustering
    Spectral Clustering
    Hierarchical Clustering
    Expectation-Maximization (EM)
  Dimension Reduction
    Principal Component Analysis (PCA)
    Linear Discriminant Analysis (LDA)
Reinforcement Learning
  Markov
    Model Based
      Iterative Value
      Iteraive Policy
    Temporal Difference
      Q-learning
      SARSA
  Evolution
    Rules
      Learning Classifiers
      XCS
    Optimizer
      Stochastic Gradient
      Genetic Algorithm