In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of th...
Bayesian Model Averaging (BMA) is well known for improving predictive accuracy by averaging inferences over all models in the model space. However, Markov chain Monte Carlo (MCMC)...
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
: The rapid progresses in human genome project and biotechnologies result in the sheer volume of datasets associated with in-depth scientific knowledge. Metabolomics is defined as ...