Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression

Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression

Abstract Objectives This paper describes the use of machine learning techniques to implement a Bayesian approach to modelling the dependency between offence data and environmental factors such as demographic characteristics and spatial location. The main goal of this paper is to provide a fully prob...

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Bibliographic Details
Main Authors: Roman Marchant, Sebastian Haan, Garner Clancey, Sally Cripps
Format: Article
Language:English
Published: Springer 2018-06-01
Series:Security Informatics
Subjects:
Semi-parametric regression
Crime rates
Machine learning
Bayesian methods
Gaussian process
Online Access:http://link.springer.com/article/10.1186/s13388-018-0030-x

Internet

http://link.springer.com/article/10.1186/s13388-018-0030-x

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