An Approach to Criminal Suspect Prediction Software using Machine Learning Classifiers

Ashima Arya, Mitu Sehgal, Neha Bhatia, Nitisha Aggarwal, Shiraz Khurana
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引用次数: 1

Abstract

The goal and the objective of this project is to predict the suspect of criminal and its location by analyzing criminal records and finding criminal hotspots. Investigations in India regarding larceny are very futile in nature and seldom result in apprehension of the criminal. Our software is for police officials to lead their investigation effectively and work towards capturing the unrighteous using data analytics thereby uncovering theft and criminal trends. Such trends lead to uncovering dimensions for an investigation which are difficult to recognize through manual inspection techniques. Such software is not only helpful for the police for effective and smart work in case of low-profile crimes but also the increase in arrests for larceny would ultimately lead to low crime rate and a lawful society. The inclusion of machine learning technique such as KNN technique is used to suspect the criminal by analyzing its data. Through the use of such software for police work in the hope of reduction in crime rate is a progressive step forward for Digital India.
基于机器学习分类器的犯罪嫌疑人预测软件研究
该项目的目标和目的是通过分析犯罪记录,寻找犯罪热点,预测犯罪嫌疑人及其所在位置。在印度,关于盗窃的调查本质上是徒劳的,很少导致罪犯被捕。我们的软件是为警察官员有效地领导他们的调查,并致力于利用数据分析捕捉不正当的行为,从而发现盗窃和犯罪趋势。这样的趋势导致了难以通过人工检查技术识别的调查维度的揭示。这样的软件不仅有助于警察有效和聪明地处理低调的犯罪案件,而且还会增加对盗窃案的逮捕,最终导致低犯罪率和法治社会。利用KNN技术等机器学习技术,通过分析数据进行犯罪嫌疑。通过在警察工作中使用这样的软件,希望减少犯罪率,这是数字印度的一个进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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