Category:Machine learning

A

• ► Applied machine learning‎ (1 C, 50 P)
• ► Artificial neural networks‎ (2 C, 155 P)

B

• ► Bayesian networks‎ (12 P)

C

• ► Classification algorithms‎ (3 C, 83 P)
• ► Cluster analysis‎ (2 C, 18 P)
• ► Computational learning theory‎ (21 P)
• ► Artificial intelligence conferences‎ (20 P)
• ► Signal processing conferences‎ (5 P)

D

• ► Data mining and machine learning software‎ (1 C, 92 P)
• ► Datasets in machine learning‎ (1 C, 7 P)
• ► Deep learning‎ (38 P)
• ► Dimension reduction‎ (1 C, 40 P)

E

• ► Ensemble learning‎ (13 P)
• ► Evolutionary algorithms‎ (4 C, 46 P, 2 F)

G

• ► Genetic programming‎ (13 P)

I

• ► Inductive logic programming‎ (5 P)

K

• ► Kernel methods for machine learning‎ (1 C, 15 P)

L

• ► Latent variable models‎ (2 C, 25 P)
• ► Learning in computer vision‎ (5 P)
• ► Log-linear models‎ (2 P)
• ► Loss functions‎ (9 P)

M

• ► Machine learning algorithms‎ (1 C, 58 P)
• ► Machine learning portal‎ (1 P)
• ► Machine learning task‎ (7 P)
• ► Markov models‎ (2 C, 53 P)

O

• ► Ontology learning (computer science)‎ (2 P)

R

• ► Machine learning researchers‎ (100 P)

S

• ► Semisupervised learning‎ (1 P)
• ► Statistical natural language processing‎ (1 C, 35 P)
• ► Structured prediction‎ (1 C, 4 P)
• ► Supervised learning‎ (2 P)
• ► Support vector machines‎ (9 P)

U

• ► Unsupervised learning‎ (13 P)

• Machine learning

*

• List of datasets for machine learning research
• Portal:Machine learning
• Outline of machine learning

A

• Action model learning
• Active learning (machine learning)
• Adversarial machine learning
• AIVA
• AIXI
• Algorithm selection
• Algorithmic bias
• Algorithmic inference
• Anomaly detection
• Appen (company)
• Apprenticeship learning
• Associative classifier
• Automated machine learning

B

• Bag-of-words model
• Ball tree
• Base rate
• Bayesian interpretation of kernel regularization
• Bayesian optimization
• Bayesian regret
• Bayesian structural time series
• Bias–variance tradeoff
• BigDL
• Binary classification
• Bing Predicts
• Bongard problem
• Bradley–Terry model

C

• Caffe (software)
• Catastrophic interference
• Category utility
• Center for Biological and Computational Learning
• CIML community portal
• Cleverbot
• Cognitive robotics
• Committee machine
• Computational learning theory
• Concept drift
• Concept learning
• Conditional random field
• Confusion matrix
• Connectionist temporal classification
• Constrained conditional model
• Convolutional neural network
• Coupled pattern learner
• Cross-entropy method
• Cross-validation (statistics)
• Curse of dimensionality

D

• Darkforest
• Data exploration
• Data pre-processing
• Dataiku
• Decision list
• Deeplearning4j
• Developmental robotics
• Dimensionality reduction
• Discriminative model
• Document classification
• Documenting Hate
• Domain adaptation

E

• Eager learning
• Early stopping
• Elastic matching
• Empirical risk minimization
• End-to-end reinforcement learning
• Error tolerance (PAC learning)
• Evaluation of binary classifiers
• Evolutionary programming
• Evolvability (computer science)
• Expectation propagation
• Explanation-based learning

F

• Feature (machine learning)
• Feature engineering
• Feature hashing
• Feature learning
• Feature scaling
• Formal concept analysis

G

• Generative model
• Genetic algorithm
• Glossary of artificial intelligence
• Grammar induction
• Granular computing

H

• Highway network
• Hyperparameter (machine learning)
• Hyperparameter optimization

I

• Inauthentic text
• Inductive bias
• Inductive probability
• Inductive programming
• Inferential theory of learning
• Instance selection
• Instance-based learning
• Instantaneously trained neural networks
• Isotropic position

J

• Journal of Machine Learning Research

K

• Kernel density estimation
• Kernel embedding of distributions
• Knowledge integration

L

• Labeled data
• Large margin nearest neighbor
• Lazy learning
• Learnable function class
• Learning automaton
• Learning to rank
• Learning with errors
• Leave-one-out error
• Life-time of correlation
• Linear predictor function
• Linear separability
• Local case-control sampling

M

• M-Theory (learning framework)
• Logic learning machine
• Machine Learning (journal)
• Machine learning control
• Machine learning in bioinformatics
• Manifold regularization
• The Master Algorithm
• Matrix regularization
• Matthews correlation coefficient
• Meta learning (computer science)
• Mixture model
• Mountain car problem
• Movidius
• Multi-armed bandit
• Multi-task learning
• Multilinear principal component analysis
• Multilinear subspace learning
• Multimodal sentiment analysis
• Multiple instance learning
• Multiple-instance learning
• Multiplicative weight update method
• Multitask optimization
• Multivariate adaptive regression splines

N

• Native-language identification
• Nearest neighbor search
• Neural modeling fields
• Novelty detection

O

• Occam learning
• Offline learning
• OpenAI Five
• OpenNN
• Overfitting

P

• Paraphrasing (computational linguistics)
• Parity learning
• Pattern language (formal languages)
• Pattern recognition
• Predictive learning
• Predictive state representation
• Preference learning
• Prior knowledge for pattern recognition
• Proactive learning
• Proaftn
• Probability matching
• Product of experts
• Programming by example
• Proximal gradient methods for learning

Q

• Qloo
• Quantum machine learning
• Query-level feature

R

• Rademacher complexity
• RAMnets
• Random forest
• Random indexing
• Random projection
• Relational data mining
• Representer theorem
• Right to explanation
• Robot learning
• Rule induction

S

• Sample complexity
• Savi Technology
• Semantic analysis (machine learning)
• Semantic folding
• Semi-supervised learning
• Sequence labeling
• Similarity learning
• Solomonoff's theory of inductive inference
• Sparse dictionary learning
• Spike-and-slab variable selection
• Stability (learning theory)
• Statistical classification
• Statistical learning theory
• Statistical relational learning
• Stochastic block model
• Structural risk minimization
• Structured sparsity regularization
• Subclass reachability
• Supervised learning

T

• Time series
• Timeline of machine learning
• Training, validation, and test sets
• Transduction (machine learning)
• Transfer learning
• Trax Retail

U

• Ugly duckling theorem
• Uncertain data
• Uniform convergence in probability
• Universal portfolio algorithm