Difference between revisions of "Repositories & Other Algorithms"
| Line 33: | Line 33: | ||
* [http://en.wikipedia.org/wiki/Manifold_alignment Manifold alignment] | * [http://en.wikipedia.org/wiki/Manifold_alignment Manifold alignment] | ||
* [http://en.wikipedia.org/wiki/Minimum_redundancy_feature_selection Minimum redundancy feature selection] | * [http://en.wikipedia.org/wiki/Minimum_redundancy_feature_selection Minimum redundancy feature selection] | ||
| − | * [ | + | * [http://en.wikipedia.org/wiki/Mixture_of_experts Mixture of experts] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Multiple_kernel_learning Multiple kernel learning] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Non-negative_matrix_factorization Non-negative matrix factorization] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Online_machine_learning Online machine learning] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Out-of-bag_error Out-of-bag error] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Prefrontal_cortex_basal_ganglia_working_memory Prefrontal cortex basal ganglia working memory] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/PVLV PVLV - primary value learned value] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Q-learning Q-learning] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Quadratic_unconstrained_binary_optimization Quadratic unconstrained binary optimization] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Query-level_feature Query-level feature] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Quickprop Quickprop] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Radial_basis_function_network Radial basis function network] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Randomized_weighted_majority_algorithm Randomized weighted majority algorithm] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Reinforcement_learning Reinforcement learning] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Repeated_incremental_pruning_to_produce_error_reduction_(RIPPER) Repeated incremental pruning to produce error reduction (RIPPER)] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Rprop Rprop] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Rule-based_machine_learning Rule-based machine learning] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Skill_chaining Skill chaining] |
* [[Sparse PCA]] | * [[Sparse PCA]] | ||
* [[State–action–reward–state–action]] | * [[State–action–reward–state–action]] | ||
Revision as of 09:01, 20 May 2018
Algorithms with Wikipedia pages...
- Almeida–Pineda recurrent backpropagation
- ALOPEX
- Backpropagation
- Bootstrap aggregating
- CN2 algorithm
- Constructing skill trees
- Dehaene–Changeux model
- Diffusion map
- Dominance-based rough set approach
- Dynamic time warping
- Error-driven learning
- Evolutionary multimodal optimization
- Expectation–maximization algorithm
- FastICA
- Forward–backward algorithm
- GeneRec
- Genetic Algorithm for Rule Set Production
- Growing self-organizing map
- HEXQ
- Hyper basis function network
- IDistance
- K-nearest neighbors algorithm
- Kernel methods for vector output
- Kernel principal component analysis
- Leabra
- Linde–Buzo–Gray algorithm
- Local outlier factor
- Logic learning machine
- LogitBoost
- Manifold alignment
- Minimum redundancy feature selection
- Mixture of experts
- Multiple kernel learning
- Non-negative matrix factorization
- Online machine learning
- Out-of-bag error
- Prefrontal cortex basal ganglia working memory
- PVLV - primary value learned value
- Q-learning
- Quadratic unconstrained binary optimization
- Query-level feature
- Quickprop
- Radial basis function network
- Randomized weighted majority algorithm
- Reinforcement learning
- Repeated incremental pruning to produce error reduction (RIPPER)
- Rprop
- Rule-based machine learning
- Skill chaining
- Sparse PCA
- State–action–reward–state–action
- Stochastic gradient descent
- Structured kNN
- T-distributed stochastic neighbor embedding
- Temporal difference learning
- Wake-sleep algorithm
- Weighted majority algorithm (machine learning)
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