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Improved method of classification algorithms for crime prediction

The growing availability of information technologies has enabled law enforcement agencies to collect detailed data about various crimes. Classification is the procedure of finding a model (or function) that depicts and distinguishes data classes or notions, with the end goal of having the ability to...

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Main Authors: Babakura, Abba, Sulaiman, Md. Nasir, Yusuf, Mahmud Ahmad
Format: Conference or Workshop Item
Language:English
Published: IEEE 2014
Online Access:http://psasir.upm.edu.my/id/eprint/48204/1/Improved%20method%20of%20classification%20algorithms%20for%20crime%20prediction.pdf
http://psasir.upm.edu.my/id/eprint/48204/
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spelling my.upm.eprints.482042016-08-04T05:17:16Z http://psasir.upm.edu.my/id/eprint/48204/ Improved method of classification algorithms for crime prediction Babakura, Abba Sulaiman, Md. Nasir Yusuf, Mahmud Ahmad The growing availability of information technologies has enabled law enforcement agencies to collect detailed data about various crimes. Classification is the procedure of finding a model (or function) that depicts and distinguishes data classes or notions, with the end goal of having the ability to utilize the model to predict the crime labels. In this research classification is applied to crime dataset to predict the 'crime category' for diverse states of the United States of America (USA). The crime data set utilized within this research is real in nature, it was gathered from socio-economic data from 1990 US census. Law enforcement data from 1990 US LEMAS survey, and from the 1995 FBI UCR. This paper compares two different classification algorithms namely - Naïve Bayesian and Back Propagation (BP) for predicting 'Crime Category' for distinctive states in USA. The result from the analysis demonstrated that Naïve Bayesian calculation out performed BP calculation and attained the accuracy of 90.2207% for group 1 and 94.0822% for group 2. This clearly indicates that Naïve Bayesian calculation is supportive for prediction in diverse states in USA. IEEE 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/48204/1/Improved%20method%20of%20classification%20algorithms%20for%20crime%20prediction.pdf Babakura, Abba and Sulaiman, Md. Nasir and Yusuf, Mahmud Ahmad (2014) Improved method of classification algorithms for crime prediction. In: International Symposium on Biometrics and Security Technologies (ISBAST 2014), 26-27 Aug. 2014, Kuala Lumpur, Malaysia. (pp. 250-255). 10.1109/ISBAST.2014.7013130
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The growing availability of information technologies has enabled law enforcement agencies to collect detailed data about various crimes. Classification is the procedure of finding a model (or function) that depicts and distinguishes data classes or notions, with the end goal of having the ability to utilize the model to predict the crime labels. In this research classification is applied to crime dataset to predict the 'crime category' for diverse states of the United States of America (USA). The crime data set utilized within this research is real in nature, it was gathered from socio-economic data from 1990 US census. Law enforcement data from 1990 US LEMAS survey, and from the 1995 FBI UCR. This paper compares two different classification algorithms namely - Naïve Bayesian and Back Propagation (BP) for predicting 'Crime Category' for distinctive states in USA. The result from the analysis demonstrated that Naïve Bayesian calculation out performed BP calculation and attained the accuracy of 90.2207% for group 1 and 94.0822% for group 2. This clearly indicates that Naïve Bayesian calculation is supportive for prediction in diverse states in USA.
format Conference or Workshop Item
author Babakura, Abba
Sulaiman, Md. Nasir
Yusuf, Mahmud Ahmad
spellingShingle Babakura, Abba
Sulaiman, Md. Nasir
Yusuf, Mahmud Ahmad
Improved method of classification algorithms for crime prediction
author_facet Babakura, Abba
Sulaiman, Md. Nasir
Yusuf, Mahmud Ahmad
author_sort Babakura, Abba
title Improved method of classification algorithms for crime prediction
title_short Improved method of classification algorithms for crime prediction
title_full Improved method of classification algorithms for crime prediction
title_fullStr Improved method of classification algorithms for crime prediction
title_full_unstemmed Improved method of classification algorithms for crime prediction
title_sort improved method of classification algorithms for crime prediction
publisher IEEE
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/48204/1/Improved%20method%20of%20classification%20algorithms%20for%20crime%20prediction.pdf
http://psasir.upm.edu.my/id/eprint/48204/
_version_ 1643834106009616384
score 13.211869

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