Crime Analysis on Spatial Domain Using Machine Learning

Abstract

Criminal activities in varied forms are present in society, aggravated by social, economic, political, cultural, and religious issues. Crimes can have an impact on a nation's quality of life, economic prosperity, and reputation. The incidence of crime and the modes of criminal activity have grown as technology has advanced, as have the preventive methods. Good quality data facilitates applications of different machine learning techniques and other algorithms which can be used to analyze the data to obtain predictions which would help law enforcement officials to prevent crime at best or to provide sufficient information to guide the police personnel to the appropriate criminal. In this chapter, different approaches that make use of different machine learning algorithms such as linear regression, logistic regression, Naïve Bayes have been proposed for crime analysis in the spatial domain. These algorithms were applied to various datasets and the chosen methodology turned out to be impeccable as the accuracy was quite high.