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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Criminal Justice Forecasts of Risk: A Machine Learning Approach

Criminal Justice Forecasts of Risk: A Machine Learning Approach

Berk, Richard

Paperback

Series: Springerbriefs in Computer Science

ApplicationsGeneral ComputersProbability & Statistics

ISBN10: 1461430844
ISBN13: 9781461430841
Publisher: Springer Nature
Published: Apr 10 2012
Pages: 115
Weight: 0.40
Height: 0.30 Width: 6.00 Depth: 9.00
Language: English
Machine learning and nonparametric function estimation procedures can be effectively used in forecasting. One important and current application is used to make forecasts of future dangerousness to inform criminal justice decision. Examples include the decision to release an individual on parole, determination of the parole conditions, bail recommendations, and sentencing. Since the 1920s, risk assessments of various kinds have been used in parole hearings, but the current availability of large administrative data bases, inexpensive computing power, and developments in statistics and computer science have increased their accuracy and applicability. In this book, these developments are considered with particular emphasis on the statistical and computer science tools, under the rubric of supervised learning, that can dramatically improve these kinds of forecasts in criminal justice settings. The intended audience is researchers in the social sciences and data analysts in criminal justice agencies.

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