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.
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Produktdetaljer
ISBN
9783030022723
Publisert
2018
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter