machine learning
Főnév
machine learning (tsz. machine learnings)
- machine learning - Szótár.net (en-hu)
- machine learning - Sztaki (en-hu)
- machine learning - Merriam–Webster
- machine learning - Cambridge
- machine learning - WordNet
- machine learning - Яндекс (en-ru)
- machine learning - Google (en-hu)
- machine learning - Wikidata
- machine learning - Wikipédia (angol)
Sablon:short description Sablon:dynamic list Sablon:machine learning bar the following outline is provided as an overview of and topical guide to machine learning:
machine learning – a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.[1] in 1959, arthur samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed".[2] machine learning involves the study and construction of algorithms that can learn from and make predictions on data.[3] these algorithms operate by building a model from an example training set of input observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
what type of thing is machine learning?
- an academic discipline
- a branch of science
- an applied science
- a subfield of computer science
- a branch of artificial intelligence
- a subfield of soft computing
- application of statistics
- a subfield of computer science
- an applied science
paradigms of machine learning
- supervised learning - where the model is trained on labeled data.
- unsupervised learning - where the model tries to identify patterns in unlabeled data
- reinforcement learning - where the model learns to make decisions by receiving rewards or penalties
applications of machine learning
- applications of machine learning
- bioinformatics
- biomedical informatics
- computer vision
- customer relationship management –
- data mining
- earth sciences
- email filtering
- inverted pendulum – balance and equilibrium system.
- natural language processing (nlp)
- pattern recognition
- recommendation system
- collaborative filtering
- content-based filtering
- hybrid recommender systems (collaborative and content-based filtering)
- search engine
- social engineering
machine learning hardware
machine learning tools
machine learning frameworks
proprietary machine learning frameworks
- amazon machine learning
- microsoft azure machine learning studio
- distbelief – replaced by tensorflow
open source machine learning frameworks
- apache singa
- apache mxnet
- caffe
- pytorch
- mlpack
- tensorflow
- torch
- cntk
- accord.net
- jax
- mlj.jl – a machine learning framework for julia
machine learning libraries
machine learning algorithms
- 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
- 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
- markov chain monte carlo (mcmc)
- 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
- 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)
machine learning methods
instance-based algorithm
- k-nearest neighbors algorithm (knn)
- learning vector quantization (lvq)
- self-organizing map (som)
- logistic regression
- ordinary least squares regression (olsr)
- linear regression
- stepwise regression
- multivariate adaptive regression splines (mars)
- regularization algorithm
- classifiers
dimensionality reduction
- canonical correlation analysis (cca)
- factor analysis
- feature extraction
- feature selection
- independent component analysis (ica)
- linear discriminant analysis (lda)
- multidimensional scaling (mds)
- non-negative matrix factorization (nmf)
- partial least squares regression (plsr)
- principal component analysis (pca)
- principal component regression (pcr)
- projection pursuit
- sammon mapping
- t-distributed stochastic neighbor embedding (t-sne)
ensemble learning
- adaboost
- boosting
- bootstrap aggregating (bagging)
- ensemble averaging – process of creating multiple models and combining them to produce a desired output, as opposed to creating just one model. frequently an ensemble of models performs better than any individual model, because the various errors of the models "average out."
- gradient boosted decision tree (gbdt)
- gradient boosting machine (gbm)
- random forest
- stacked generalization (blending)
meta-learning
reinforcement learning
- q-learning
- state–action–reward–state–action (sarsa)
- temporal difference learning (td)
- learning automata
supervised learning
- averaged one-dependence estimators (aode)
- artificial neural network
- 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
- conditional random field
- anova
- quadratic classifiers
- k-nearest neighbor
- boosting
- sprint
- bayesian networks
- hidden markov models
bayesian
- bayesian knowledge base
- naive bayes
- gaussian naive bayes
- multinomial naive bayes
- averaged one-dependence estimators (aode)
- bayesian belief network (bbn)
- bayesian network (bn)
decision tree algorithms
decision tree algorithm
- decision tree
- classification and regression tree (cart)
- iterative dichotomiser 3 (id3)
- c4.5 algorithm
- c5.0 algorithm
- chi-squared automatic interaction detection (chaid)
- decision stump
- conditional decision tree
- id3 algorithm
- random forest
- sliq
linear classifier
- fisher's linear discriminant
- linear regression
- logistic regression
- multinomial logistic regression
- naive bayes classifier
- perceptron
- support vector machine
unsupervised learning
- expectation-maximization algorithm
- vector quantization
- generative topographic map
- information bottleneck method
- association rule learning algorithms
artificial neural networks
association rule learning
hierarchical clustering
cluster analysis
- birch
- dbscan
- expectation–maximization (em)
- fuzzy clustering
- hierarchical clustering
- k-means clustering
- k-medians
- mean-shift
- optics algorithm
anomaly detection
semi-supervised learning
- active learning – special case of semi-supervised learning in which a learning algorithm is able to interactively query the user (or some other information source) to obtain the desired outputs at new data points.[4][5]
- generative models
- low-density separation
- graph-based methods
- co-training
- transduction
deep learning
- deep belief networks
- deep boltzmann machines
- deep convolutional neural networks
- deep recurrent neural networks
- hierarchical temporal memory
- generative adversarial network
- transformer
- stacked auto-encoders
other machine learning methods and problems
- anomaly detection
- association rules
- bias-variance dilemma
- classification
- clustering
- data pre-processing
- empirical risk minimization
- feature engineering
- feature learning
- learning to rank
- occam learning
- online machine learning
- pac learning
- regression
- reinforcement learning
- semi-supervised learning
- statistical learning
- structured prediction
- unsupervised learning
- vc theory
machine learning research
history of machine learning
machine learning projects
machine learning projects
machine learning organizations
machine learning organizations
machine learning conferences and workshops
- artificial intelligence and security (aisec) (co-located workshop with ccs)
- conference on neural information processing systems (nips)
- ecml pkdd
- international conference on machine learning (icml)
- ml4all (machine learning for all)
machine learning publications
books on machine learning
- mathematics for machine learning
- hands-on machine learning scikit-learn, keras, and tensorflow
- the hundred-page machine learning book
machine learning journals
persons influential in machine learning
- alberto broggi
- andrei knyazev
- andrew mccallum
- andrew ng
- anuraag jain
- armin b. cremers
- ayanna howard
- barney pell
- ben goertzel
- ben taskar
- bernhard schölkopf
- brian d. ripley
- christopher g. atkeson
- corinna cortes
- demis hassabis
- douglas lenat
- eric xing
- ernst dickmanns
- geoffrey hinton – co-inventor of the backpropagation and contrastive divergence training algorithms
- hans-peter kriegel
- hartmut neven
- heikki mannila
- ian goodfellow – father of generative & adversarial networks
- jacek m. zurada
- jaime carbonell
- jeremy slovak
- jerome h. friedman
- john d. lafferty
- john platt – invented smo and platt scaling
- julie beth lovins
- jürgen schmidhuber
- karl steinbuch
- katia sycara
- leo breiman – invented bagging and random forests
- lise getoor
- luca maria gambardella
- léon bottou
- marcus hutter
- mehryar mohri
- michael collins
- michael i. jordan
- michael l. littman
- nando de freitas
- ofer dekel
- oren etzioni
- pedro domingos
- peter flach
- pierre baldi
- pushmeet kohli
- ray kurzweil
- rayid ghani
- ross quinlan
- salvatore j. stolfo
- sebastian thrun
- selmer bringsjord
- sepp hochreiter
- shane legg
- stephen muggleton
- steve omohundro
- tom m. mitchell
- trevor hastie
- vasant honavar
- vladimir vapnik – co-inventor of the svm and vc theory
- yann lecun – invented convolutional neural networks
- yasuo matsuyama
- yoshua bengio
- zoubin ghahramani
see also
- outline of artificial intelligence
- outline of robotics
- accuracy paradox
- action model learning
- activation function
- activity recognition
- adaline
- adaptive neuro fuzzy inference system
- adaptive resonance theory
- additive smoothing
- adjusted mutual information
- aiva
- aixi
- alchemyapi
- alexnet
- algorithm selection
- algorithmic inference
- algorithmic learning theory
- alphago
- alphago zero
- alternating decision tree
- apprenticeship learning
- causal markov condition
- competitive learning
- concept learning
- decision tree learning
- differentiable programming
- distribution learning theory
- eager learning
- end-to-end reinforcement learning
- error tolerance (pac learning)
- explanation-based learning
- feature
- glove
- hyperparameter
- inferential theory of learning
- learning automata
- learning classifier system
- learning rule
- learning with errors
- m-theory (learning framework)
- machine learning control
- machine learning in bioinformatics
- margin
- markov chain geostatistics
- markov chain monte carlo (mcmc)
- markov information source
- markov logic network
- markov model
- markov random field
- markovian discrimination
- maximum-entropy markov model
- multi-armed bandit
- multi-task learning
- multilinear subspace learning
- multimodal learning
- multiple instance learning
- multiple-instance learning
- never-ending language learning
- offline learning
- parity learning
- population-based incremental learning
- predictive learning
- preference learning
- proactive learning
- proximal gradient methods for learning
- semantic analysis
- similarity learning
- sparse dictionary learning
- stability (learning theory)
- statistical learning theory
- statistical relational learning
- tanagra
- transfer learning
- variable-order markov model
- version space learning
- waffles
- weka
- loss function
- low-energy adaptive clustering hierarchy
other
- anne o'tate
- ant colony optimization algorithms
- anthony levandowski
- anti-unification (computer science)
- apache flume
- apache giraph
- apache mahout
- apache singa
- apache spark
- apache systemml
- aphelion (software)
- arabic speech corpus
- archetypal analysis
- arthur zimek
- artificial ants
- artificial bee colony algorithm
- artificial development
- artificial immune system
- astrostatistics
- averaged one-dependence estimators
- bag-of-words model
- balanced clustering
- ball tree
- base rate
- bat algorithm
- baum–welch algorithm
- bayesian hierarchical modeling
- bayesian interpretation of kernel regularization
- bayesian optimization
- bayesian structural time series
- bees algorithm
- behavioral clustering
- bernoulli scheme
- bias–variance tradeoff
- biclustering
- bigml
- binary classification
- bing predicts
- bio-inspired computing
- biogeography-based optimization
- biplot
- bondy's theorem
- bongard problem
- bradley–terry model
- brownboost
- brown clustering
- burst error
- cbcl (mit)
- ciml community portal
- cma-es
- cure data clustering algorithm
- cache language model
- calibration (statistics)
- canonical correspondence analysis
- canopy clustering algorithm
- cascading classifiers
- category utility
- cellcognition
- cellular evolutionary algorithm
- chi-square automatic interaction detection
- chromosome (genetic algorithm)
- classifier chains
- cleverbot
- clonal selection algorithm
- cluster-weighted modeling
- clustering high-dimensional data
- clustering illusion
- coboosting
- cobweb (clustering)
- cognitive computer
- cognitive robotics
- collostructional analysis
- common-method variance
- complete-linkage clustering
- computer-automated design
- concept class
- concept drift
- conference on artificial general intelligence
- conference on knowledge discovery and data mining
- confirmatory factor analysis
- confusion matrix
- congruence coefficient
- connect (computer system)
- consensus clustering
- constrained clustering
- constrained conditional model
- constructive cooperative coevolution
- correlation clustering
- correspondence analysis
- cortica
- coupled pattern learner
- cross-entropy method
- cross-validation (statistics)
- crossover (genetic algorithm)
- cuckoo search
- cultural algorithm
- cultural consensus theory
- curse of dimensionality
- dadisp
- darpa lagr program
- darkforest
- dartmouth workshop
- darwintunes
- data mining extensions
- data exploration
- data pre-processing
- data stream clustering
- dataiku
- davies–bouldin index
- decision boundary
- decision list
- decision tree model
- deductive classifier
- deepart
- deepdream
- deep web technologies
- defining length
- dendrogram
- dependability state model
- detailed balance
- determining the number of clusters in a data set
- detrended correspondence analysis
- developmental robotics
- diffbot
- differential evolution
- discrete phase-type distribution
- discriminative model
- dissociated press
- distributed r
- dlib
- document classification
- documenting hate
- domain adaptation
- doubly stochastic model
- dual-phase evolution
- dunn index
- dynamic bayesian network
- dynamic markov compression
- dynamic topic model
- dynamic unobserved effects model
- edlut
- elki
- edge recombination operator
- effective fitness
- elastic map
- elastic matching
- elbow method (clustering)
- emergent (software)
- encog
- entropy rate
- erkki oja
- eurisko
- european conference on artificial intelligence
- evaluation of binary classifiers
- evolution strategy
- evolution window
- evolutionary algorithm for landmark detection
- evolutionary algorithm
- evolutionary art
- evolutionary music
- evolutionary programming
- evolvability (computer science)
- evolved antenna
- evolver (software)
- evolving classification function
- expectation propagation
- exploratory factor analysis
- f1 score
- flame clustering
- factor analysis of mixed data
- factor graph
- factor regression model
- factored language model
- farthest-first traversal
- fast-and-frugal trees
- feature selection toolbox
- feature hashing
- feature scaling
- feature vector
- firefly algorithm
- first-difference estimator
- first-order inductive learner
- fish school search
- fisher kernel
- fitness approximation
- fitness function
- fitness proportionate selection
- fluentd
- folding@home
- formal concept analysis
- forward algorithm
- fowlkes–mallows index
- frederick jelinek
- frrole
- functional principal component analysis
- gatto
- glimmer
- gary bryce fogel
- gaussian adaptation
- gaussian process
- gaussian process emulator
- gene prediction
- general architecture for text engineering
- generalization error
- generalized canonical correlation
- generalized filtering
- generalized iterative scaling
- generalized multidimensional scaling
- generative adversarial network
- generative model
- genetic algorithm
- genetic algorithm scheduling
- genetic algorithms in economics
- genetic fuzzy systems
- genetic memory (computer science)
- genetic operator
- genetic programming
- genetic representation
- geographical cluster
- gesture description language
- geworkbench
- glossary of artificial intelligence
- glottochronology
- golem (ilp)
- google matrix
- grafting (decision trees)
- gramian matrix
- grammatical evolution
- granular computing
- graphlab
- graph kernel
- gremlin (programming language)
- growth function
- humant (humanoid ant) algorithm
- hammersley–clifford theorem
- harmony search
- hebbian theory
- hidden markov random field
- hidden semi-markov model
- hierarchical hidden markov model
- higher-order factor analysis
- highway network
- hinge loss
- holland's schema theorem
- hopkins statistic
- hoshen–kopelman algorithm
- huber loss
- ircf360
- ian goodfellow
- ilastik
- ilya sutskever
- immunocomputing
- imperialist competitive algorithm
- inauthentic text
- incremental decision tree
- induction of regular languages
- inductive bias
- inductive probability
- inductive programming
- influence diagram
- information harvesting
- information gain in decision trees
- information gain ratio
- inheritance (genetic algorithm)
- instance selection
- intel realsense
- interacting particle system
- interactive machine translation
- international joint conference on artificial intelligence
- international meeting on computational intelligence methods for bioinformatics and biostatistics
- international semantic web conference
- iris flower data set
- island algorithm
- isotropic position
- item response theory
- iterative viterbi decoding
- joone
- jabberwacky
- jaccard index
- jackknife variance estimates for random forest
- java grammatical evolution
- joseph nechvatal
- jubatus
- julia (programming language)
- junction tree algorithm
- k-svd
- k-means++
- k-medians clustering
- k-medoids
- knime
- kxen inc.
- k q-flats
- kaggle
- kalman filter
- katz's back-off model
- kernel adaptive filter
- kernel density estimation
- kernel eigenvoice
- kernel embedding of distributions
- kernel method
- kernel perceptron
- kernel random forest
- kinect
- klaus-robert müller
- kneser–ney smoothing
- knowledge vault
- knowledge integration
- libsvm
- lpboost
- labeled data
- languageware
- language identification in the limit
- language model
- large margin nearest neighbor
- latent dirichlet allocation
- latent class model
- latent semantic analysis
- latent variable
- latent variable model
- lattice miner
- layered hidden markov model
- learnable function class
- least squares support vector machine
- leslie p. kaelbling
- linear genetic programming
- linear predictor function
- linear separability
- lingyun gu
- linkurious
- lior ron (business executive)
- list of genetic algorithm applications
- list of metaphor-based metaheuristics
- list of text mining software
- local case-control sampling
- local independence
- local tangent space alignment
- locality-sensitive hashing
- log-linear model
- logistic model tree
- low-rank approximation
- low-rank matrix approximations
- matlab
- mimic (immunology)
- mxnet
- mallet (software project)
- manifold regularization
- margin-infused relaxed algorithm
- margin classifier
- mark v. shaney
- massive online analysis
- matrix regularization
- matthews correlation coefficient
- mean shift
- mean squared error
- mean squared prediction error
- measurement invariance
- medoid
- meemix
- melomics
- memetic algorithm
- meta-optimization
- mexican international conference on artificial intelligence
- michael kearns (computer scientist)
- minhash
- mixture model
- mlpy
- models of dna evolution
- moral graph
- mountain car problem
- movidius
- multi-armed bandit
- multi-label classification
- multi expression programming
- multiclass classification
- multidimensional analysis
- multifactor dimensionality reduction
- multilinear principal component analysis
- multiple correspondence analysis
- multiple discriminant analysis
- multiple factor analysis
- multiple sequence alignment
- multiplicative weight update method
- multispectral pattern recognition
- mutation (genetic algorithm)
- mysteryvibe
- n-gram
- nominate (scaling method)
- native-language identification
- natural language toolkit
- natural evolution strategy
- nearest-neighbor chain algorithm
- nearest centroid classifier
- nearest neighbor search
- neighbor joining
- nest labs
- netminer
- netowl
- neural designer
- neural engineering object
- neural modeling fields
- neural network software
- neurosolutions
- neuroevolution
- neuroph
- niki.ai
- noisy channel model
- noisy text analytics
- nonlinear dimensionality reduction
- novelty detection
- nuisance variable
- one-class classification
- onnx
- opennlp
- optimal discriminant analysis
- oracle data mining
- orange (software)
- ordination (statistics)
- overfitting
- progol
- psipred
- pachinko allocation
- pagerank
- parallel metaheuristic
- parity benchmark
- part-of-speech tagging
- particle swarm optimization
- path dependence
- pattern language (formal languages)
- peltarion synapse
- perplexity
- persian speech corpus
- picas (app)
- pietro perona
- pipeline pilot
- piranha (software)
- pitman–yor process
- plate notation
- polynomial kernel
- pop music automation
- population process
- portable format for analytics
- predictive model markup language
- predictive state representation
- preference regression
- premature convergence
- principal geodesic analysis
- prior knowledge for pattern recognition
- prisma (app)
- probabilistic action cores
- probabilistic context-free grammar
- probabilistic latent semantic analysis
- probabilistic soft logic
- probability matching
- probit model
- product of experts
- programming with big data in r
- proper generalized decomposition
- pruning (decision trees)
- pushpak bhattacharyya
- q methodology
- qloo
- quality control and genetic algorithms
- quantum artificial intelligence lab
- queueing theory
- quick, draw!
- r (programming language)
- rada mihalcea
- rademacher complexity
- radial basis function kernel
- rand index
- random indexing
- random projection
- random subspace method
- ranking svm
- rapidminer
- rattle gui
- raymond cattell
- reasoning system
- regularization perspectives on support vector machines
- relational data mining
- relationship square
- relevance vector machine
- relief (feature selection)
- renjin
- repertory grid
- representer theorem
- reward-based selection
- richard zemel
- right to explanation
- roboearth
- robust principal component analysis
- ruleml symposium
- rule induction
- rules extraction system family
- sas (software)
- snns
- spss modeler
- subclu
- sample complexity
- sample exclusion dimension
- santa fe trail problem
- savi technology
- schema (genetic algorithms)
- search-based software engineering
- selection (genetic algorithm)
- self-service semantic suite
- semantic folding
- semantic mapping (statistics)
- semidefinite embedding
- sense networks
- sensorium project
- sequence labeling
- sequential minimal optimization
- shattered set
- shogun (toolbox)
- silhouette (clustering)
- simhash
- simrank
- similarity measure
- simple matching coefficient
- simultaneous localization and mapping
- sinkov statistic
- sliced inverse regression
- snakes and ladders
- soft independent modelling of class analogies
- soft output viterbi algorithm
- solomonoff's theory of inductive inference
- solveit software
- spectral clustering
- spike-and-slab variable selection
- statistical machine translation
- statistical parsing
- statistical semantics
- stefano soatto
- stephen wolfram
- stochastic block model
- stochastic cellular automaton
- stochastic diffusion search
- stochastic grammar
- stochastic matrix
- stochastic universal sampling
- stress majorization
- string kernel
- structural equation modeling
- structural risk minimization
- structured sparsity regularization
- structured support vector machine
- subclass reachability
- sufficient dimension reduction
- sukhotin's algorithm
- sum of absolute differences
- sum of absolute transformed differences
- swarm intelligence
- switching kalman filter
- symbolic regression
- synchronous context-free grammar
- syntactic pattern recognition
- td-gammon
- timit
- teaching dimension
- teuvo kohonen
- textual case-based reasoning
- theory of conjoint measurement
- thomas g. dietterich
- thurstonian model
- topic model
- tournament selection
- training, test, and validation sets
- transiogram
- trax image recognition
- trigram tagger
- truncation selection
- tucker decomposition
- uima
- upgma
- ugly duckling theorem
- uncertain data
- uniform convergence in probability
- unique negative dimension
- universal portfolio algorithm
- user behavior analytics
- vc dimension
- vigra
- validation set
- vapnik–chervonenkis theory
- variable-order bayesian network
- variable kernel density estimation
- variable rules analysis
- variational message passing
- varimax rotation
- vector quantization
- vicarious (company)
- viterbi algorithm
- vowpal wabbit
- waca clustering algorithm
- wpgma
- ward's method
- weasel program
- whitening transformation
- winnow (algorithm)
- win–stay, lose–switch
- witness set
- wolfram language
- wolfram mathematica
- writer invariant
- xgboost
- yooreeka
- zeroth (software)
- ↑ http://www.britannica.com/ebchecked/topic/1116194/machine-learning Sablon:tertiary source
- ↑ phil simon (march 18, 2013). too big to ignore: the business case for big data. wiley. p. 89. ISBN 978-1-118-63817-0. Check date values in:
|date=
(help) - ↑ (1998) „glossary of terms”. machine learning 30, 271–274. o. DOI:10.1023/a:1007411609915.
- ↑ Sablon:citation
- ↑ Lua-hiba a(z) package.lua modulban a(z) 80. sorban: module 'Module:Citation/CS1/Suggestions' not found