Abstract

Abstract: The aim of this study is to develop a machine learning-based application that can analyze crime data across different districts in India and categorize them as high, moderate, or low based on the frequency of crimes. Based on the frequency of particular crimes in particular districts we will suggest necessary preventive measures and also recommend some precautions before visiting a particular crime hotspot. The methodology involved using a Logistic regression model for crime classification, followed by k-means clustering to group districts based on their crime rates. The results of the study demonstrated the efficacy of the machine learning model in accurately classifying crimes. The original contribution of this research lies in the development of an application that provides users with valuable insights into the crime rates in different districts

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