User:Dgoulier/Books/Wikipedia Machine Learning
 | The Wikimedia Foundation's book rendering service has been withdrawn. Please upload your Wikipedia book to one of the external rendering services. |
 | You can still create and edit a book design using the Book Creator and upload it to an external rendering service:
|
| This user book is a user-generated collection of Wikipedia articles that can be easily saved, rendered electronically, and ordered as a printed book. If you are the creator of this book and need help, see Help:Books (general tips) and WikiProject Wikipedia-Books (questions and assistance). Edit this book: Book Creator · Wikitext Order a printed copy from: PediaPress [ About ] [ Advanced ] [ FAQ ] [ Feedback ] [ Help ] [ WikiProject ] [ Recent Changes ] | ||||||||
Wikipedia Machine Learning[edit]
- Accuracy paradox
- Action model learning
- Active learning (machine learning)
- Adversarial machine learning
- Algorithm Selection
- Algorithmic inference
- AlphaGo
- Apprenticeship learning
- Bag-of-words model
- Ball tree
- Base rate
- Bayesian interpretation of kernel regularization
- Bayesian optimization
- Bayesian structural time series
- Bias–variance tradeoff
- Binary classification
- Bing Predicts
- Bongard problem
- Bradley–Terry model
- Catastrophic interference
- Category utility
- CBCL (MIT)
- Computational learning theory
- Concept learning
- Conditional random field
- Confusion matrix
- Constrained conditional model
- Coupled pattern learner
- Cross-entropy method
- Cross-validation (statistics)
- Curse of dimensionality
- Darkforest
- Data pre-processing
- Dataiku
- Decision list
- Deep feature synthesis
- Deeplearning4j
- DeepMind
- Dimensionality reduction
- Discriminative model
- Document classification
- Domain adaptation
- Eager learning
- Early stopping
- Elastic matching
- Empirical risk minimization
- Ensembles of classifiers
- Error Tolerance (PAC learning)
- Evaluation of binary classifiers
- Evolutionary programming
- Evolvability (computer science)
- Expectation propagation
- Explanation-based learning
- Feature (machine learning)
- Feature engineering
- Feature hashing
- Feature learning
- Feature scaling
- Feature vector
- Formal concept analysis
- Generative model
- Genetic algorithm
- Hyperparameter optimization
- Inductive bias
- Inductive probability
- Inductive programming
- Inductive transfer
- Inferential theory of learning
- Instance selection
- Instance-based learning
- Instantaneously trained neural networks
- Isotropic position
- Kernel density estimation
- Kernel embedding of distributions
- Kernel random forest
- Knowledge integration
- Knowledge Vault
- Large margin nearest neighbor
- Lazy learning
- Learnable function class
- Learning automata
- Learning to rank
- Learning with errors
- Leave-one-out error
- Linear predictor function
- Linear separability
- List of datasets for machine learning research
- Local case-control sampling
- Logic learning machine
- M-Theory (learning framework)
- Machine learning
- Machine learning control
- Manifold regularization
- Matrix regularization
- Matthews correlation coefficient
- Meta learning (computer science)
- Mixture model
- Mountain Car
- Movidius
- Multi-armed bandit
- Multi-task learning
- Multilinear principal component analysis
- Multilinear subspace learning
- Multiple instance learning
- Multiple-instance learning
- Multiplicative Weight Update Method
- Multivariate adaptive regression splines
- MysteryVibe
- Native-language identification
- Nearest neighbor search
- Neural modeling fields
- Occam learning
- Offline learning
- OpenNN
- Outline of machine learning
- Overfitting
- Parity learning
- Pattern language (formal languages)
- Pattern recognition
- Predictive learning
- Predictive state representation
- Preference learning
- Prior knowledge for pattern recognition
- Proactive learning
- Probability matching
- Product of experts
- Proximal gradient methods for learning
- Random indexing
- Random projection
- Relational data mining
- Representer theorem
- Sample complexity
- Semantic analysis (machine learning)
- Semantic folding
- Semi-supervised learning
- Sequence labeling
- Similarity learning
- Singular statistical model
- Skymind
- 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
- Test set
- The Master Algorithm
- Timeline of machine learning
- Transduction (machine learning)
- Trax Image Recognition
- Ugly duckling theorem
- Uncertain data
- Uniform convergence in probability
- Universal portfolio algorithm
- Unsupervised learning
- User behavior analytics
- Vanishing gradient problem
- Version space learning