title: Vbmp: variational Bayesian Multinomial Probit Regression for multi-class classification in R.
abstract: CONCLUSIONS
  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 one main function and reasonable default values for optional parameters, vbmp combines flexibility with ease of usage as is demonstrated on a breast cancer microarray study.
  
  
  BACKGROUND
  The R library vbmp implementing this method is part of Bioconductor and can be downloaded from http://www.dcs.gla.ac.uk/~girolami
authors.affiliation: Medical Statistics Unit, Department of Medicine and Public Health, Second University of Napoli, Italy. nicola.lama@unina2.it
authors.forename: Nicola
authors.initials: N
authors.lastname: Lama
authors.forename: Mark
authors.initials: M
authors.lastname: Girolami
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D009363:Neoplasm Proteins / Q000032:analysis*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D011381:Programming Languages; D012044:Regression Analysis; D012984:Software
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins