Comparison of Algorithms for Crime Analysis
Dhananjay Raghav · International Journal for Research in Applied Science and Engineering Technology · 2020
There are nearly thousands of crimes that happen every day. There are many algorithms for calculating an area's crime rate but there is no best algorithm for calculating an area's crime rate, depending on the algorithm's accuracy and time complexity. So, we've taken four unsupervised clustering algorithms K means clustering, agglomerative clustering, gaussian clustering, density-based spatial clustering algorithms to compare them based on the accuracy of the algorithms on a given collection of data to figure out the best algorithm to figure out the crime rate of a given region. This paper essentially presents a comparative study of all four clustering algorithms, and it is found that k means clustering algorithm is the best clustering algorithm for calculating an area's crime rate on the given data set.