Crime Type and Occurrence Prediction Using Machine Learning Algorithm

Authors

  • P. Kalyan Chakravarthi Assistant professor, Department of CSE (AI/ML &CS), Godavari institute of engineering and technology. Author
  • M. Sai Sumanth Department of CSE (AI/ML &CS), Godavari institute of engineering and technology. Author
  • G. Sunil Kumar Department of CSE (AI/ML &CS), Godavari institute of engineering and technology. Author
  • P. Ajay Kumar Department of CSE (AI/ML &CS), Godavari institute of engineering and technology. Author
  • M. Viswa Pranay Department of CSE (AI/ML &CS), Godavari institute of engineering and technology. Author

Keywords:

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

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. 

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References

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Published

29.02.2024

How to Cite

Crime Type and Occurrence Prediction Using Machine Learning Algorithm. (2024). International Journal of Psychosocial Rehabilitation, 28(1), 17-24. http://65.2.176.223/psychosocial/index.php/ijpr/article/view/5