Machine learning in forensic applications

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2019-04-01
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Carriquiry, Alicia
Hofmann, Heike
Tai, Xiao Hui
VanderPlas, Susan
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Center for Statistics and Applications in Forensic Evidence
The Center for Statistics and Applications in Forensic Evidence (CSAFE) carries out research on the scientific foundations of forensic methods, develops novel statistical methods and transfers knowledge and technological innovations to the forensic science community. We collaborate with more than 80 researchers and across six universities to drive solutions to support our forensic community partners with accessible tools, open-source databases and educational opportunities.
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Statistics
As leaders in statistical research, collaboration, and education, the Department of Statistics at Iowa State University offers students an education like no other. We are committed to our mission of developing and applying statistical methods, and proud of our award-winning students and faculty.
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Center for Statistics and Applications in Forensic EvidenceStatistics
Abstract

The 2009 National Academy of Sciences report found pattern‐evidence disciplines to be rife with subjectivity. In the decade since, machine learning methods have been developed to try to address that issue. By Alicia Carriquiry, Heike Hofmann, Xiao Hui Tai and Susan VanderPlas.

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This following article is published as Carriquiry, Alicia, Heike Hofmann, Xiao Hui Tai, and Susan VanderPlas. "Machine learning in forensic applications." Significance 16, no. 2 (2019): 29-35. Posted with permission of CSAFE.

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Tue Jan 01 00:00:00 UTC 2019
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