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Criminal Justice Forecasts of Risk - Richard Berk
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A Machine Learning Approach 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. Criminal Justice Forecasts of Risk: 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. Forecasting Future Dangerousness Machine Learning Parole Probation Public Safety Random Forecasts Risk Assessment Sentencing Statistical Learning C Probability and Statistics in Computer Science Artificial Intelligence (incl. Robotics) Statis, Springer New York

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Criminal Justice Forecasts of Risk - Richard Berk
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Richard Berk:
Criminal Justice Forecasts of Risk - neues Buch

ISBN: 9781461430858

ID: 9781461430858

A Machine Learning Approach 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. Criminal Justice Forecasts of Risk: 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. Datenverarbeitung / Anwendungen / Mathematik, Statistik Intelligenz / Künstliche Intelligenz KI Künstliche Intelligenz - AI AI ( Künstliche Intelligenz ) Statistik COMPUTERS / Intelligence (AI) & Semantics, Springer-Verlag Gmbh

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Criminal Justice Forecasts of Risk:A Machine Learning Approach SpringerBriefs in Computer Science. 2012. Auflage Richard Berk Criminal Justice Forecasts of Risk:A Machine Learning Approach SpringerBriefs in Computer Science. 2012. Auflage Richard Berk eBooks > Fachthemen & Wissenschaft > Mathematik, Springer New York

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Criminal Justice Forecasts of Risk ab 35.49 EURO A Machine Learning Approach SpringerBriefs in Computer Science. 2012. Auflage Criminal Justice Forecasts of Risk ab 35.49 EURO A Machine Learning Approach SpringerBriefs in Computer Science. 2012. Auflage eBooks > Fachthemen & Wissenschaft > Mathematik

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A Machine Learning Approach, 2012, eBook Download (PDF), eBooks, [PU: Springer New York]

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Criminal Justice Forecasts of Risk
Autor:

Richard Berk

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Detailangaben zum Buch - Criminal Justice Forecasts of Risk


EAN (ISBN-13): 9781461430858
ISBN (ISBN-10): 1461430852
Erscheinungsjahr: 2012
Herausgeber: Springer New York
115 Seiten
Sprache: eng/Englisch

Buch in der Datenbank seit 13.09.2012 02:46:05
Buch zuletzt gefunden am 12.10.2017 02:27:53
ISBN/EAN: 9781461430858

ISBN - alternative Schreibweisen:
1-4614-3085-2, 978-1-4614-3085-8


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