Reamostragem e dados faltantes
18 métodos nesta família.
Em destaque
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 Bootstrap BCa (Correção de Viés e Aceleração)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 biBootstrap de Bloco (Bloco Móvel e Estacionário)Block bootstrap is a resampling method for dependent, autocorrelated time-series data: instead of resampling single observations, it resamples whole blocks of consecutive observatiInferência BootstrapBootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requireSimulação BootstrapBootstrap 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
Percurso de leitura
Os métodos fundamentais mais referenciados deste tópico, pela ordem em que foram desenvolvidos — um ponto de partida se está a começar agora.
Todos os métodos 18
Bagging (Bootstrap Aggregating)Bagging EnsembleBootstrap BCa (Correção de Viés e Aceleração)Bootstrap de Bloco (Bloco Móvel e Estacionário)Inferência BootstrapSimulação BootstrapBootstrap Duplo (Iterado)EM AlgorithmRegressão Linear de EnsembleEstimativa por JackknifeAnálise de MediaçãoImputação MúltiplaBagging OnlineBootstrap ParamétricoTeste de Permutação (Randomização)Robust BaggingNaive Bayes AutossupervisionadoBagging Semi-supervisionado