Machine Learning Risk Assessments in Criminal Justice Settings / / by Richard Berk

• Autore: Berk Richard
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
• Edizione: 1st ed. 2019.
• Descrizione fisica: 1 online resource (184 pages)
• Disciplina: 364.22
• Soggetto topico: Artificial intelligence; Mathematical statistics; Criminology; Research; Data mining; Artificial Intelligence; Probability and Statistics in Computer Science; Quantitative Criminology; Data Mining and Knowledge Discovery
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 1 Getting Started -- 2 Some Important Background Material -- 3 A Conceptual Introduction Classification and Forecasting -- 4 A More Formal Treatment of Classification and Forecasting -- 5 Tree-Based Forecasting Methods -- 6 Transparency, Accuracy and Fairness -- 7 Real Applications -- 8 Implementation -- 9 Some Concluding Observations About Actuarial Justice and More.
• Sommario/riassunto: 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.
• Titolo autorizzato: Machine Learning Risk Assessments in Criminal Justice Settings
• ISBN: 3-030-02272-2
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910337835903321
• Lo trovi qui: Univ. Federico II