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Towards a ‘smart’ cost–benefit tool: using machine learning to predict the costs of criminal justice policy interventions

Crossref DOI link: https://doi.org/10.1186/s40163-018-0086-4

Published Online: 2018-10-12

Published Print: 2018-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Manning, Matthew https://orcid.org/0000-0002-1622-4936
Wong, Gabriel T. W. https://orcid.org/0000-0001-9572-1561
Graham, Timothy

Ranbaduge, Thilina

Christen, Peter

Taylor, Kerry

Wortley, Richard

Makkai, Toni

Skorich, Pierre
Funding

Funding for this research was provided by:

Economic & Social Research Council (ES/L007223/1)

Australian National University (Cross College Grant)

Jill Dando Institute of Security and Crime Science
License Information

Text and Data Mining valid from 2018-10-12
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Article History

Received: 23 November 2017

Accepted: 28 September 2018

First Online: 12 October 2018

Change Date: 29 November 2018

Change Type: Correction

Change Details: The original version of the article contained an error in the funding section and name of an author. The correction funding note should be: This project was funded by the Economic & Social Research Council grant (ESRC Reference: ES/L007223/1) titled ‘University Consortium for Evidence-Based Crime Reduction’, the Australian National University’s Cross College Grant and the Jill Dando Institute of Security and Crime Science.