The NeuroBayes neural network package

被引：196

作者：

Feindt, M

Kerzel, U

机构：

[1] Univ Karlsruhe, Inst Expt Kernphys, D-7500 Karlsruhe, Germany

[2] Phi T Phys Informat Technol GmbH, D-76139 Karlsruhe, Germany

来源：

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2006年 / 559卷 / 01期

关键词：

Bayes; neural network; classification; density reconstruction; data-mining; preprocessing;

D O I：

10.1016/j.nima.2005.11.166

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Detailed analysis of correlated data plays a vital role in modern analyses. We present a sophisticated neural network package based on Bayesian statistics which can be used for both classification and event-by-event prediction of the complete probability density distribution for continuous quantities. The network provides numerous possibilities to automatically preprocess the input variables and uses advanced regularisation and pruning techniques to essentially eliminate the risk of overtraining. Examples from physics and industry are given. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：190 / 194

页数：5