Literature DB >> 20627632

Implementing statistical learning methods through Bayesian networks (Part 2): Bayesian evaluations for results of black toner analyses in forensic document examination.

A Biedermann1, F Taroni, S Bozza, W D Mazzella.   

Abstract

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software. Copyright Â
© 2010 Elsevier Ireland Ltd. All rights reserved.

Year:  2010        PMID: 20627632     DOI: 10.1016/j.forsciint.2010.05.001

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  2 in total

1.  Forensic Discrimination Potential of Blue, Black, Green, and Red Colored Fountain Pen Inks Commercially Used in Pakistan, by UV/Visible Spectroscopy, Thin Layer Chromatography, and Fourier Transform Infrared Spectroscopy.

Authors:  Mehwish Sharif; Madeeha Batool; Sohail Chand; Zahoor Hussain Farooqi; Syed Azhar Ali Shah Tirmazi; Makshoof Athar
Journal:  Int J Anal Chem       Date:  2019-01-06       Impact factor: 1.885

2.  Using Bayesian networks to guide the assessment of new evidence in an appeal case.

Authors:  Nadine M Smit; David A Lagnado; Ruth M Morgan; Norman E Fenton
Journal:  Crime Sci       Date:  2016-05-25
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.