Recognizing crime patterns is crucial for being better prepared to respond to criminal behaviour. Assessed crime statistics from the city of Indore that has been collected from the Indore Polices publicly available website in this study. The goal is to estimate which type of crime is most likely to occur in Indore at a particular time and location. Artificial intelligence and machine learning have become more significant in crime detection and prevention. Applied the Nave Bayes, K-nearest neighbour, and linear regression approaches to analyse crime data using the same limited set of variables on the Communities and Crime Dataset from Indore. In terms of overall performance, the Nave Bayes approach performs well in compare to the other machine learning algorithms.

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