A program for the Bayesian Neural Network in the ROOT framework

Abstract
We present a Bayesian Neural Network algorithm implemented in the TMVA package (Hoecker et al., 2007 [1]), within the ROOT framework (Brun and Rademakers, 1997 [2]). Comparing to the conventional utilization of Neural Network as discriminator, this new implementation has more advantages as a non-parametric regression tool, particularly for fitting probabilities. It provides functionalities including cost function selection, complexity control and uncertainty estimation. An example of such app...

Title of program: TMVA-BNN
Catalogue Id: AEJX_v1_0

Nature of problem
Non-parametric fitting of multivariate distributions.

Versions of this program held in the CPC repository in Mendeley Data
AEJX_v1_0; TMVA-BNN; 10.1016/j.cpc.2011.07.019

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)