What are some popular Machine Learning Methods?

• Parametric classifiers and regressors:
  • Perceptron
  • Support vector machines
    • Including kernel support vector machines
  • Artificial neurons, including logistic regression
  • Neural networks and deep learning
    • Including convolutional neural networks and recurrent neural networks
  • LDA and Fischer’s discriminant classifiers
  • Conditional and Markovian random fields (for structures or sequences)
  • Hidden markov model (for structures or sequences)
  • Direct model regressors, including linear regression, and quadratic regression.
• Non-parametric Classifiers
  • KNN
  • Decision tree
  • Random Forest
  • Random Fern
  • Maximum A Posteriori methods
    • Especially the naive Bayes classifier
• Pattern Discovery and Clustering
  • Partial Component Analysis
  • Independent component analysis
  • Neural networks and deep learning
    • Specifically deep belief networks
  • Hierarchical clustering
  • Expectation-Maximization
  • K-means (sometimes included in EM)
  • Mean shift
• Generative
  • Neural networks and deep learning
  • Especially deep belief networks and generative adversarial networks
  • Hidden Markov Models
  • Conditional and markovian random fields