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The studentized bootstrap, also called bootstrap-t, is computed analogously to the standard confidence interval, but replaces the quantiles from the normal or student approximation by the quantiles from the bootstrap distribution of the Student's t-test (see Davison and Hinkley 1997, equ. 5.7 p. 194 and Efron and Tibshirani 1993 equ 12.22, p. 160):
The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1]
Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the ...
The beta negative binomial distribution; The Boltzmann distribution, a discrete distribution important in statistical physics which describes the probabilities of the various discrete energy levels of a system in thermal equilibrium.
This is a list of computing and IT acronyms, initialisms and abbreviations. ... BOOTP—Bootstrap Protocol; ... CS—Cable Select;
Model selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. [1] In the context of machine learning and more generally statistical analysis, this may be the selection of a statistical model from a set of candidate models, given data.
Bootstrap paradox (also ontological paradox): You send information/an object to your past self, but you only have that information/object because in the past, you ...
A row of slot machines in Las Vegas. In probability theory and machine learning, the multi-armed bandit problem (sometimes called the K-[1] or N-armed bandit problem [2]) is a problem in which a decision maker iteratively selects one of multiple fixed choices (i.e., arms or actions) when the properties of each choice are only partially known at the time of allocation, and may become better ...