Variational Bayesian multinomial probit model with Gaussian process classification on mice protein expression level data
نویسندگان
چکیده
منابع مشابه
Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors
It is well known in the statistics literature that augmenting binary and polychotomous response models with gaussian latent variables enables exact Bayesian analysis viaGibbs sampling from the parameter posterior. By adopting such a data augmentation strategy, dispensing with priors over regression coefficients in favor of gaussian process (GP) priors over functions, and employing variational a...
متن کاملVariational Multinomial Logit Gaussian Process
Gaussian process prior with an appropriate likelihood function is a flexible non-parametric model for a variety of learning tasks. One important and standard task is multi-class classification, which is the categorization of an item into one of several fixed classes. A usual likelihood function for this is the multinomial logistic likelihood function. However, exact inference with this model ha...
متن کاملMultinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data
We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior...
متن کاملNested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior distribution, and the increase of the number of unknown latent variables as the number of target classes grows. Expectation propagation (EP) has proven to be a very accurate method for approximate...
متن کاملvbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R
SUMMARY Vbmp is an R package for Gaussian Process classification of data over multiple classes. It features multinomial probit regression with Gaussian Process priors and estimates class posterior probabilities employing fast variational approximations to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination. Being equipped with only...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ??????
سال: 2023
ISSN: ['2218-2055', '1812-5409']
DOI: https://doi.org/10.5351/kjas.2023.36.2.115