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- Bayesian_additive_regression_kernels abstract "Bayesian additive regression kernels (BARK) is a non-parametric statistical model for regression and statistical classification.The unknown mean function is represented as a weighted sum of kernel functions, which is constructed by a prior usingalpha-stable Lévy random fields.[citation needed] This leads to a specification of a joint prior distribution for the number of kernels, kernel regression coefficients and kernel location parameters. It can be shown that the alpha-stable prior on the kernel regression coefficients may be approximated by t distributions. With a heavy tail prior distribution on the kernel regression coefficients and a finite support on the kernel location parameter, BARK achieves sparse representations. The shape parameters in the kernel functions capture the non-linear interactions of the variables, which can be used for feature selection. A reversible-jump Markov chain Monte Carlo algorithm is developed to make posterior inference on the unknown mean function, and the R package is available on CRAN. For binary classification using a probit link, the model can be augmented with latent normal variables and hence the same method for Gaussian noise applies in the classification problem.".
- Bayesian_additive_regression_kernels wikiPageID "18650668".
- Bayesian_additive_regression_kernels wikiPageRevisionID "514344135".
- Bayesian_additive_regression_kernels hasPhotoCollection Bayesian_additive_regression_kernels.
- Bayesian_additive_regression_kernels subject Category:Non-parametric_Bayesian_methods.
- Bayesian_additive_regression_kernels subject Category:Statistical_classification.
- Bayesian_additive_regression_kernels type Ability105616246.
- Bayesian_additive_regression_kernels type Abstraction100002137.
- Bayesian_additive_regression_kernels type Cognition100023271.
- Bayesian_additive_regression_kernels type Know-how105616786.
- Bayesian_additive_regression_kernels type Method105660268.
- Bayesian_additive_regression_kernels type Non-parametricBayesianMethods.
- Bayesian_additive_regression_kernels type PsychologicalFeature100023100.
- Bayesian_additive_regression_kernels comment "Bayesian additive regression kernels (BARK) is a non-parametric statistical model for regression and statistical classification.The unknown mean function is represented as a weighted sum of kernel functions, which is constructed by a prior usingalpha-stable Lévy random fields.[citation needed] This leads to a specification of a joint prior distribution for the number of kernels, kernel regression coefficients and kernel location parameters.".
- Bayesian_additive_regression_kernels label "Bayesian additive regression kernels".
- Bayesian_additive_regression_kernels sameAs m.04gt3qw.
- Bayesian_additive_regression_kernels sameAs Q4874462.
- Bayesian_additive_regression_kernels sameAs Q4874462.
- Bayesian_additive_regression_kernels sameAs Bayesian_additive_regression_kernels.
- Bayesian_additive_regression_kernels wasDerivedFrom Bayesian_additive_regression_kernels?oldid=514344135.
- Bayesian_additive_regression_kernels isPrimaryTopicOf Bayesian_additive_regression_kernels.