List of machine learning concepts
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(Redirected from Machine learning algorithms)
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This list is incomplete; you can help by expanding it.
Contents
Supervised learning[edit]
- AODE
- Artificial neural network
- Bayesian statistics
- Case-based reasoning
- Gaussian process regression
- Gene expression programming
- Group method of data handling (GMDH)
- Inductive logic programming
- Instance-based learning
- Lazy learning
- Learning Automata
- Learning Vector Quantization
- Logistic Model Tree
- Minimum message length (decision trees, decision graphs, etc.)
- Probably approximately correct learning (PAC) learning
- Ripple down rules, a knowledge acquisition methodology
- Symbolic machine learning algorithms
- Support vector machines
- Random Forests
- Ensembles of classifiers
- Ordinal classification
- Information fuzzy networks (IFN)
- Conditional Random Field
- ANOVA
- Linear classifiers
- Quadratic classifiers
- k-nearest neighbor
- Boosting
- Decision trees
- Bayesian networks
- Hidden Markov models
Unsupervised learning[edit]
- Expectation-maximization algorithm
- Vector Quantization
- Generative topographic map
- Information bottleneck method
Artificial neural network[edit]
Association rule learning[edit]
Hierarchical clustering[edit]
Cluster analysis[edit]
Outlier Detection[edit]
Semi-supervised learning[edit]
| This section is empty. You can help by adding to it. (February 2015) |
Reinforcement learning[edit]
Deep learning[edit]
- Deep belief networks
- Deep Boltzmann machines
- Deep Convolutional neural networks
- Deep Recurrent neural networks
- Hierarchical temporal memory

