The Use of Machine Learning for the Prediction of Crime Type and Occurrence

Abstract

These days, criminal activity is a certain way to get yourself in hot water. Discontent at voting locations has been
fanned by a nationwide increase in criminal activity. In order to detect and react to these illegal acts, it is essential to
comprehend crime trends. This research analyzes crime data using the open-source Kaggle platform, which has been
utilized to forecast the majority of crimes as of late. The project's overarching goal is to foretell the frequency, kind,
and location of certain criminal acts. With the use of machine learning techniques like KNN and SVM, this study
improves upon earlier attempts to identify a variety of crimes. Kaggle, crime model, analysis, prediction, accuracy,
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