Újramintavételezés és hiányzó adatok
18 módszer ebben a családban.
Kiemelt
Bagging (Bootstrap Aggregating)Bagging, short for Bootstrap Aggregating, is an ensemble meta-algorithm introduced by Leo Breiman in 1996 that trains multiple copies of a base learner on independently drawn bootsBagging EnsembleBagging, short for bootstrap aggregating, is an ensemble method that reduces variance by training multiple copies of a single learning algorithm on different random subsets of the BCa Bootstrap (Bias-Corrected and Accelerated)The BCa bootstrap is a resampling method, introduced by Bradley Efron in 1987, that produces more accurate confidence intervals than the plain percentile bootstrap by applying a biBlokk Bootstrap (Mozgó Blokk és Stacionárius)Block bootstrap is a resampling method for dependent, autocorrelated time-series data: instead of resampling single observations, it resamples whole blocks of consecutive observatiBootstrap-becslésBootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requireBootstrap szimulációBootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly re
Olvasási útvonal
E témakör leggyakrabban hivatkozott alapmódszerei kidolgozásuk sorrendjében — kiindulópont, ha most ismerkedik a területtel.
Minden módszer 18
Bagging (Bootstrap Aggregating)Bagging EnsembleBCa Bootstrap (Bias-Corrected and Accelerated)Blokk Bootstrap (Mozgó Blokk és Stacionárius)Bootstrap-becslésBootstrap szimulációIterált bootstrap (Dupla bootstrap)EM-algoritmusEnsemble Linear RegressionJackknife Resampling EstimationMediációs analízisTöbbszörös imputációOnline BaggingParametrikus BootstrapPermutációs (randomizációs) tesztRobust BaggingÖnfelügyelt Naiv BayesFélfelügyelt Bagging