Crime Type and Occurrence Prediction Using Machine Learning Algorithm

1P. Kalyan Chakravarthi

2M. Sai Sumanth

3G. Sunil Kumar

4P. Ajay Kumar

5M. Viswa Pranay

1Godavari institute of engineering and technology,
2Godavari institute of engineering and technology
,
3Godavari institute of engineering and technology
,
4Godavari institute of engineering and technology
,
5Godavari institute of engineering and technology

130 Views
43 Downloads
Abstract:

As of late, crime has turned into an unmistakable way for individuals and society to experience difficulties. An irregularity in a country's populace happens when crime goes up. To assess and manage this sort of crime, it's vital to know how crime designs change over the long time. This study utilizes crime information from Kaggle open source to do a sort of crime design examination. The information is then used to think about what crime will occur straightaway. The central matter of this study is to figure out what sort of crime has the greatest effect, as well as when and where it worked out. In this work, machine learning techniques like Nave Bayes are utilized to bunch different criminal patterns into gatherings. The outcomes were exact contrasted with other comparative works.

Keywords:

Crime, Analyse, Crime patterns, Kaggle, Estimate, Naïve Bayes, Accuracy

Paper Details
Month02
Year2024
Volume28
IssueIssue 1
Pages17-24

Our Indexing Partners

Scilit
CrossRef
CiteFactor