Crime Type and Occurrence Prediction using Machine Learning Algorithm

Author(s)	Mr. Chetan Dange, Dr. Suvarna Nandyal, Mr. Ameet Bhande, Mr. Pramod Chalakapur
Country	India
Abstract	In this era of recent times, crime has become an evident way of making people and society under trouble. An increasing crime factor leads to an imbalance in the constituency of a country. In order to analyze and have a response ahead this type of criminal activities, it is necessary to understand the crime patterns. This study imposes one such crime pattern analysis by using crime data obtained from Kaggle open source which in turn used for the prediction of most recently occurring crimes. The major aspect of this project is to estimate which type of crime contributes the most along with time period and location where it has happened. Some machine learning algorithms such as Naïve Bayes is implied in this work in order to classify among various crime patterns and the accuracy achieved was comparatively high when compared to pre composed works.
Keywords	Random Forest, Support Vector Machine (SVM), and Logistic Regression.
Field	Engineering
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-08-09
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.47774

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