Skip to content

Ensemble SLRs for Forensic Evidence Comparison

Primary Author: Danica Ommen
Type: Webinar

This CSAFE webinar was held on August 25, 2022.

Presenter:
Danica Ommen
Assistant Professor – Department of Statistics, Iowa State University

Presentation Description:

To strengthen the statistical foundations of forensic evidence interpretation, likelihood ratios and Bayes factors are advocated to quantify the value of evidence. Both methods rely on formulating a statistical model, which can be challenging for complex evidence. Machine learning score-based likelihood ratios have been proposed as an alternative in those cases. Under this framework, a (dis)similarity score and its distribution under alternative propositions are estimated using pairwise comparisons, but pairwise comparisons of all the evidential objects result in dependent scores. While machine learning methods may not require distributional assumptions, most assume independence. We introduce a sampling and ensembling approach to remedy this lack of independence. We generate sets where assumptions are met to develop multiple score-based  likelihood ratios later aggregated into a final score to quantify the value of evidence.

Webinar Recording:

Read more about the study in this post

Related Resources

Forensic Footwear: A Retrospective of the Development of the MANTIS Shoe Scanning System

Forensic Footwear: A Retrospective of the Development of the MANTIS Shoe Scanning System

There currently are no shoe-scanning devices developed in the United States that can operate in a real-world, variable-weather environment in real-time. Forensics-focused groups, including the NIJ, expressed the need for…
Examiner consistency in perceptions of fingerprint minutia rarity

Examiner consistency in perceptions of fingerprint minutia rarity

Friction ridge examiners (FREs) identify distinctive features (minutiae) in fingerprints and consider how rare these observed minutiae are in their decisions about both the value of a fingerprint and whether…
Significance of image brightness levels for PRNU camera identification

Significance of image brightness levels for PRNU camera identification

A forensic investigator performing source identification on a questioned image from a crime aims to identify the unknown camera that acquired the image. On the camera sensor, minute spatial variations…
Methodological problems in every black-box study of forensic firearm comparisons

Methodological problems in every black-box study of forensic firearm comparisons

Reviews conducted by the National Academy of Sciences (2009) and the President’s Council of Advisors on Science and Technology (2016) concluded that the field of forensic firearm comparisons has not…