Built environment attributes and crime: an automated machine learning approach

Built environment attributes and crime: an automated machine learning approach

Abstract This paper presents the development of an automated machine learning approach to gain an understanding of the built environment and its relationship to crime. This involves the automatic capture of street-level photographs using Google Street View (GSV), followed by the use of supervised ma...

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Bibliographic Details
Main Authors: Kyle Dakin, Weizhi Xie, Simon Parkinson, Saad Khan, Leanne Monchuk, Ken Pease
Format: Article
Language:English
Published: BMC 2020-07-01
Series:Crime Science
Subjects:
Crime prevention
Supervised machine learning
Feature recognition
Crime analytics
Online Access:http://link.springer.com/article/10.1186/s40163-020-00122-9

Internet

http://link.springer.com/article/10.1186/s40163-020-00122-9

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