Machine Learning Risk Assessments in Criminal Justice Settings (Hardcover, 1st ed. 2019)

This book puts in one place and in accessible form Richard Berk's most recent work on forecasts of re-offending by individuals already in criminal justice custody. Using machine learning statistical procedures trained on very large datasets, an explicit introduction of the relative costs of forecasting errors as the forecasts are constructed, and an emphasis on maximizing forecasting accuracy, the author shows how his decades of research on the topic improves forecasts of risk. Criminal justice risk forecasts anticipate the future behavior of specified individuals, rather than "predictive policing" for locations in time and space, which is a very different enterprise that uses different data different data analysis tools. The audience for this book includes graduate students and researchers in the social sciences, and data analysts in criminal justice agencies. Formal mathematics is used only as necessary or in concert with more intuitive explanations.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	December 2018
First published:	2019
Authors:	Richard Berk
Dimensions:	235 x 155 x 19mm (L x W x T)
Format:	Hardcover
Pages:	178
Edition:	1st ed. 2019
ISBN-13:	978-3-03-002271-6
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Social sciences > Sociology, social studies > Crime & criminology > Offenders > General
LSN:	3-03-002271-4
Barcode:	9783030022716

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