Superviseret maskinlæring
165 metoder i denne familie.
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Aktiv læringActive learning is an iterative machine-learning paradigm in which a learning algorithm selectively queries an oracle — typically a human annotator — for labels on the most informaAktiv læring med boostingActive Learning Boosting combines the query-driven label acquisition of active learning with the weighted-ensemble logic of boosting algorithms such as AdaBoost. The model iterativActive Learning Decision TreeActive learning with a decision tree combines the interpretable structure of a CART-style tree with a query strategy that selects the most informative unlabeled instances for humanAktiv Læring Fødereret LæringFederated Active Learning combines the annotation-efficiency of active learning with the privacy-preserving decentralization of federated learning. A shared global model is trainedAktiv Læring Gaussisk BlandingsmodelActive Learning Gaussian Mixture Model combines an iterative query strategy with a Gaussian Mixture Model learner. The algorithm selects the most informative unlabeled points — typActive Learning Gradient BoostingActive Learning Gradient Boosting combines the powerful predictive accuracy of gradient boosted trees with an active learning loop that selects the most informative unlabeled examp
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This topic's most-referenced foundational methods, in the order they were developed — a place to start if you're new here.
Alle metoder 165
Aktiv læringAktiv læring med boostingActive Learning Decision TreeAktiv Læring Fødereret LæringAktiv Læring Gaussisk BlandingsmodelActive Learning Gradient BoostingAktiv læring K-nærmeste naboerActive Learning LightGBMAktiv Læring Lineær RegressionAktiv læring One-class SVMAktiv læring med selvovervåget læringActive Learning Stacking EnsembleSupport Vector Machine med aktiv læringActive Learning Voting EnsembleAdaBoostBoostingBoosting EnsembleBorda-tællingsaggregeringCatBoostKollaborativ filtreringKonform forudsigelseBeslutningstræDempster-Shafer FusionEmerging Pattern MiningEnsemble Active LearningEnsemble Decision TreeEnsemble Federated LearningEnsemble Few-Shot LearningEnsemble Gaussian Mixture ModelEnsemble Gaussian ProcessEnsemble Gradient BoostingEnsemble K-Nearest NeighborsEnsemble Metric LearningEnsemble Naive BayesEnsemble One-Class SVMEnsemble Online LearningEnsemble Selv-superviseret LæringEnsemble semi-superviseret læringEnsemble Support Vector MachineEnsemble Transfer LearningEkstra TræerFew-shot LearningFP-Growth (Frequent Pattern Growth)Generaliseret Additiv Model (GAM)Uafhængig komponentanalyse (ICA)IsomapK-Nærmeste NaboerLabel PropagationLightGBMLineær Diskriminant Analyse (LDA)Lineær regression (ML)LOESS / LOWESS Lokal RegressionFlertalsafstemningMultivariate Adaptive Regression Splines (MARS)Matrix CompletionMetrisk LæringMulti-layer Perceptron (MLP)Naive BayesNon-negativ Matrixfaktorisering (NMF)Online Active LearningOnline BoostingOnline Decision TreeOnline Federated LearningOnline Few-shot LearningOnline FP-growthOnline Gaussian Mixture ModelOnline Gaussisk ProcesOnline Gradient BoostingOnline K-Nearest NeighborsOnline læringOnline LightGBMOnline Lineær RegressionOnline Metric LearningOnline Naive BayesOnline One-Class SVMOnline Random ForestOnline Self-supervised LearningOnline semi-superviseret læringOnline Support Vector MachineOnline Transfer LearningOnline Voting EnsembleDetektion af uden-distributionsdataPartiel mindste kvadraters regression (PLS)Policy Gradient-metoderQ-LearningKvadratisk diskriminantanalyse (QDA)Random ForestRegression- og smoothing-splinesRegulariseret BoostingRegulariseret CatBoostReguleret beslutningstræRegulariseret fødereret læringRegulariseret Few-Shot LæringRegulæriseret Gaussisk ProcesRegulariseret gradient-boostingRegulariseret k-Nærmeste NaboerRegulariseret Naiv BayesRegulæriseret Online LæringRegulariseret Random ForestRegulariseret semisuperviseret læringRegulariseret Support Vector MachineRegulariseret TransferlæringRobust Active LearningRobust BoostingRobust Decision TreeRobust Federated LearningRobust Gaussian Mixture ModelRobust Gaussian ProcessRobust metrisk læringRobust One-Class SVMRobust Online LæringRobust Random ForestRobust Stacking EnsembleRobust Support Vector-maskineRobust stemmeensembleRegelinduktion (RIPPER)Selv-superviseret aktiv læringSelv-superviseret BoostingSelv-overvåget beslutningstræSelv-superviseret fødereret læringSelv-superviseret få-skuds læringSelv-superviseret Gaussisk ProcesSelvsuperviseret gradient-boostingSelv-overvåget K-nærmeste naboerSelvovervåget læringSelv-superviseret LightGBMSelv-superviseret metrisk læringSelv-overvåget One-class SVMSelvovervåget Random ForestSelf-supervised Stacking EnsembleSelv-overvåget Support Vector MachineSelv-overvåget transfer learningSemi-supervised Active LearningSemi-supervised BoostingSemi-superviseret CatBoostSemi-overvåget BeslutningstræSemi-supervised Federated LearningSemi-supervised Few-shot LearningSemi-supervised FP-growthSemi-supervised Gaussian Mixture ModelSemi-supervised Gaussisk ProcesSemi-overvåget Gradient BoostingSemi-superviseret K-Nærmeste NaboerSemi-supervised LearningSemi-supervised LightGBMSemi-overvåget lineær regressionSemi-supervised Metric LearningSemi-superviseret Naive BayesSemi-supervised One-class SVMSemi-superviseret Online IndlæringSemi-supervised Random ForestSemi-supervised Stacking EnsembleSemi-supervised Support Vector MachineSemi-supervised Transfer LearningSemi-supervised Voting EnsembleSemi-supervised XGBoostSekventiel mønsterudvindingStablet GeneraliseringStackingStokastisk gradientnedstigning (SGD)Support Vector Machine (Klassifikation)Support Vector RegressionOverførselslæringStemmeensembleXGBoost