A Novel Clustering & Machine Learning Algorithm for Crime Rate Prediction and Analysis

The security implications of gathering and analyzing data on criminal activity in researcher’s everyday lives are not well understood. Forecasting and analyzing crime rates involves mining a database of criminal offenses for hidden trends. Everyday criminal behavior in different regions of the globe may be predicted by user approach. They can make inferences about the data set using data mining and machine learning techniques. This method facilitates a quicker resolution to the crime. Setting information is offered instead of an explanation for the crime. To better the field of criminology, they use the K-means clustering technique and the linear regression algorithm. Crime statistics may be analyzed on a weekly or monthly basis.