List of machine learning concepts

Supervised learning

• Artificial neural network
  • Backpropagation
• Bayesian statistics
  • Naive Bayes classifier
  • Bayesian network
  • Bayesian Knowledge base
• Case-based reasoning
• Decision tree learning
• Inductive logic programming
• Gaussian process regression
• Learning Automata
• Minimum message length (decision trees, decision graphs, etc.)
• lazy learning
• instance-based learning
  • Nearest Neighbor Algorithm
• Probably approximately correct learning (PAC) learning
• Ripple down rules, a knowledge acquisition methodology
• Symbolic machine learning algorithms
• Subsymbolic machine learning algorithms
• Support vector machines
• Random Forests
• Ensembles of Classifiers
  • Bootstrap aggregating(bagging)
  • Boosting
• Ordinal Classification
• Regression analysis
• Information Fuzzy Networks (IFN)

Statistical classification

• Linear classifiers
  • Fisher's linear discriminant
  • Logistic regression
  • Naive Bayes classifier
  • Perceptron
  • Support vector machines
• Quadratic classifiers
• k-nearest neighbor
• Boosting
• Decision trees
  • Random forests
• Neural networks
• Bayesian networks
• Hidden Markov models

Unsupervised learning

• Artificial neural network
• Data clustering
• Expectation-maximization algorithm
• Self-organizing map
• Radial basis function network
• Generative topographic map
• Information bottleneck method

Association rule learning

• Apriori algorithm
• Eclat algorithm
• FP-Growth algorithm

Cluster analysis

Hierarchical clustering

• single-linkage clustering
• conceptual clustering

Partitional clustering

• K-means algorithm
• fuzzy clustering

Others

• Data Pre-processing
• Handling imbalanced datasets