This article describes the use of relatively simple, fast to run, and fully transparent decision trees to assess the interpretation of DNA profiles.
The interpretation of DNA profiles typically starts with an assessment of the number of contributors. In the last two decades, several methods have been proposed to assist with this assessment. The authors describe a relatively simple method using decision trees, that is fast to run and fully transparent to a forensic analyst. The authors use mixtures from the publicly available PROVEDIt dataset to demonstrate the performance of the method. The authors show that the performance of the method crucially depends on the performance of filters for stutter and other artefacts. The authors compare the performance of the decision tree method with other published methods for the same dataset. (Published Abstract Provided)
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