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City Crime Mapping Using Machine Learning Techniques

  • Nitish Yadav
  • Ashish KumarEmail author
  • Roheet Bhatnagar
  • Vivek Kumar Verma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

In order to prevent a crime it is very important to analyze and understand the patterns of criminal activity of that place. Police Department can work effectively and efficiently if the crime pattern is known to them. In this work, we attempted an exploratory analysis of a standard dataset in order to predict the resolution that was given for the crimes that occurred from 2003 to 2015. The dataset is obtained from San Francisco Police Department Crime Incident Reporting System. We used Machine Learning Algorithms like CART, K-NN, Gaussian Naive Bayes, and Multilayer Perceptron (MLP). Validation and cross validation were used to test the results of each technique. The experiment shows that we can obtains higher accuracy by using CART algorithm.

Keywords

Crime classification CART K-NN Gaussian Naive Bayes 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Nitish Yadav
    • 1
  • Ashish Kumar
    • 1
    Email author
  • Roheet Bhatnagar
    • 1
  • Vivek Kumar Verma
    • 2
  1. 1.Department of Computer Science and EngineeringManipal University JaipurJaipurIndia
  2. 2.Department of Information and TechnologyManipal University JaipurJaipurIndia

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