ML inayosimamiwa
165 mbinu katika familia hii.
Zilizoangaziwa
Kujifunza kwa Njia AmilifuActive 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 informaUjifunzaji Amilifu wa KuimarishaActive Learning Boosting combines the query-driven label acquisition of active learning with the weighted-ensemble logic of boosting algorithms such as AdaBoost. The model iterativMti wa Kujifunza kwa Kazi (Active Learning Decision Tree)Active 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 humanActive Learning Federated LearningFederated Active Learning combines the annotation-efficiency of active learning with the privacy-preserving decentralization of federated learning. A shared global model is trainedActive Learning Gaussian Mixture ModelActive Learning Gaussian Mixture Model combines an iterative query strategy with a Gaussian Mixture Model learner. The algorithm selects the most informative unlabeled points — typKujifunza Amilifu kwa Kuimarisha MteremkoActive 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.
Mbinu zote 165
Kujifunza kwa Njia AmilifuUjifunzaji Amilifu wa KuimarishaMti wa Kujifunza kwa Kazi (Active Learning Decision Tree)Active Learning Federated LearningActive Learning Gaussian Mixture ModelKujifunza Amilifu kwa Kuimarisha MteremkoKujifunza kwa Njia ya Kujitolea kwa Kutumia Wanajamaa-KActive Learning LightGBMRegressioni ya Kujifunza kwa Nguvu (Active Learning Linear Regression)Jifunze kwa Vitendo One-class SVMKujifunza kwa Vitendo kwa Kutumia Kujifunza Kujisimamia KwenyeweKujifunza kwa Njia Tendaji kwa Kuunganisha MbinuKujifunza Amilifu kwa Mashine ya Kusaidia VektaKujifunza kwa Vitendo kwa Kura za KikundiAdaBoostKuimarishaUimarishaji (Boosting Ensemble)Ushirikishwaji wa Hesabu ya BordaCatBoostKichujio cha KushirikianaUtabiri UlinganifuMti wa UamuziMuunganisho wa Dempster-ShaferUchimbaji wa Sampuli ZinazojitokezaUjifunzaji Amilifu wa Vikundi (Ensemble Active Learning)Njia za Mti wa Uamuzi wa EnsembleKujifunza kwa Shirikisho la PamojaUjifunzaji wa Vikundi wa Sampuli ChacheMuundo wa Mchanganyiko wa Gaussian wa EnsembleMchakato wa Gaussia wa PamojaUboreshaji wa Ensemble wa GradientEnsemble K-Nearest NeighborsMafunzo ya Ensemble Metric LearningEnsemble Naive BayesEnsemble One-class SVMKujifunza kwa pamoja mtandaoniUjifunzaji Unganishi Unaojisimamia (Ensemble Self-supervised Learning)Jifunze la Nusu-msaada la Ensemble (Ensemble Semi-supervised Learning)Mchanganyiko wa Mashine za Usaidizi wa Vigezo (Ensemble Support Vector Machine)Kujumuika kwa Kujifunza kwa Kuhamisha (Ensemble Transfer Learning)Miti ya ZiadaKujifunza kwa Kiasi Kidogo cha MifanoFP-Growth (Frequent Pattern Growth)Generalized Additive Model (GAM)Uchanganuzi wa vipengele huru (ICA)IsomapJirani-Karibu-WengiUenezaji wa LeboLightGBMUchambuzi wa Ubaguzi wa Laini (LDA)Regresi Laini (ML)LOESS / LOWESS Usanifu wa Kurekebisha wa KienyejiUpigaji Kura wa WengiNjia za Kurekebisha Kidokezo kwa Regressioni Yenye Wingi (MARS)Uamiliishaji wa MatrikiMafunzo ya vipimoPerceptroni wa Tabaka Nyingi (MLP)Naive BayesUchanganuzi wa Matrix Usio-na-Hasara (NMF)Kujifunza kwa Njia ya Kufanya Kazi MtandaoniKuimarisha MtandaoniMti wa Maamuzi wa MtandaoniUjifunzaji Unganishi wa MtandaoniKujifunza Kidogo cha MtandaoniOnline FP-growthMchanganyiko wa Gaussian mtandaoniMchakato wa Gaussia wa MtandaoniOnline Gradient BoostingK-Nearest Neighbors ya MtandaoniJifunze MtandaoniOnline LightGBMUrekebishaji wa Laini wa MtandaoniMafunzo ya Metriki ya MtandaoniNaive Bayes OnlineOnline One-Class SVMMsitu Nasibu wa MtandaoniUjifunzaji wa Kujisimamia MtandaoniKujifunza mtandaoni kwa nusu-usimamiziMashine ya Vektor Saidizi ya MtandaoniUjifunzaji wa Kuhamisha MtandaoniEnsemble Upigaji Kura MtandaoniUtambuzi wa Data Nje ya UsambazajiUsajili wa Viwango vya chini vya sehemu (PLS)Mbinu za Kielelezo cha SeraQ-LearningUchambuzi wa Kutofautisha wa Ki-Quadratic (QDA)Msitu NasibuRegression SplinesKuimarisha kwa KurekebishwaCatBoost IliyodhibitiwaRegularized Decision TreeMafunzo yaliyoimarishwa kwa njia ya shirikishiUjifunzaji wa Kishoti Kidogo UlioratibiwaRegularized Gaussian ProcessUboreshaji wa Gradient Ulioimarishwak-Nearest Neighbors IliyoimarishwaNaive Bayes IliyodhibitiwaKujifunza kwa Njia ya Mtandaoni IliyodhibitiwaMsitu wa Kawaida wa BahatishaUjifunzaji Ulioimarishwa Nusu-SimamiaSupport Vector Machine yenye RegulareshiniUhamishaji Kujifunza UliodhibitiwaMafunzo Amilifu ImaraUimarishaji ImaraMti Imara wa UamuziMafunzo Imara ya MuunganoMfumo Imara wa Mchanganyiko wa GaussianMchakato Imara wa GaussianMafunzo Imara ya UpimajiSVM Daraja Moja ImaraKujifunza Imara MtandaoniMsitu Imara wa MisituUundaji wa Kuimarisha wa Kuunganisha kwa NguvuMashine ya Vektor Saidizi Imara (Robust Support Vector Machine)Umoja wa Kupiga Kura ImaraUundaji wa Kanuni (RIPPER)Self-supervised Active LearningUboreshaji unaojifundishaMti wa Mti wa Kujifundisha PekeeKujifundisha kwa Kujitegemea kwa Njia ya ShirikishiKujifunza kwa Kujitegemea kwa Kiasi Kidogo (SSL-FSL)Self-supervised Gaussian ProcessUboreshaji wa Gradient unaojifundishaUjifundishaji wa majirani k-karibuJifunze kwa KujisimamiaTaratibu za awali za LightGBMJifunze-mwenyewe Kujifundisha kwa Kutumia vipimoSVM ya Daraja Moja inayojifundishaSelf-supervised Random ForestSelf-supervised Stacking EnsembleMashine ya Vektor Saidizi Inayojisimamia YenyeweMafunzo ya uhamishaji yanayojisimamiaKujifunza kwa Kazi kwa Nusu-UsimamiziSemi-supervised BoostingCatBoost ya Nusu-UsimamiziMti wa Maamuzi wa Nusu-MsimamiziJifunze kwa Pamoja kwa Nusu-UsimamiziKujifunza kwa Kina kidogo kwa Njia ya Nusu-SimamiziSemi-supervised FP-growthKielelezo cha Mchanganyiko wa Gaussian chenye Usimamizi KidogoMchakato wa Gaussia Nusu-simamiwaSemi-supervised Gradient BoostingUjifundishaji wa Nusu-Nusu wa Majirani-K-KaribuUjifunzaji Nusu-SimamiwaSemi-supervised LightGBMUchambuzi wa Regresi ya Laini yenye Nusu-UsimamiziJifunze kipimo cha kukabiliana na hali kwa kutumia nusu-usimamiziNaive Bayes Semi-iliyojumuSemi-supervised One-class SVMKujifunza Mtandaoni kwa Nusu-UsimamiziRandom Forest ya Nusu-MsimamiziMkusanyiko wa Kuweka Tabaka Nusu-SimamiziMashine ya Vektor Saidizi Nusu-SimamiziKujifunza kwa Kuhamisha kwa Nusu-SimamiziKupatanisha Kwa Kupiga Kura Kulisaidika kwa NusuXGBoost ya Nusu-SimamiziUchimbaji wa ruwaza mfuatanoStacked GeneralizationUwekaji juuKushuka kwa Gradient kwa Bahati Nasibu (SGD)Support Vector Machine (Uainishaji)Regression ya Vigawe TeziKujifunza kwa uhamishajiKikundi cha Kura (Voting Ensemble)XGBoost