One‐class classification with application to forensic analysis

Francesca Fortunato, Laura Anderlucci and Angela Montanari

Journal of the Royal Statistical Society Series C, 2020, vol. 69, issue 5, 1227-1249

Abstract: The analysis of broken glass is forensically important to reconstruct the events of a criminal act. In particular, the comparison between the glass fragments found on a suspect (recovered cases) and those collected at the crime scene (control cases) may help the police to identify the offender(s) correctly. The forensic issue can be framed as a one‐class classification problem. One‐class classification is a recently emerging and special classification task, where only one class is fully known (the so‐called target class), whereas information on the others is completely missing. We propose to consider Gini's classical transvariation probability as a measure of typicality, i.e. a measure of resemblance between an observation and a set of well‐known objects (the control cases). The aim of the proposed transvariation‐based one‐class classifier is to identify the best boundary around the target class, i.e. to recognize as many target objects as possible while rejecting all those deviating from this class.

Date: 2020
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