The aim of this project is advanced methods in clustering. • Comparison of the results of at least 3 methods among the presented clustering methods • Sensitivity analysis on the parameters of the used models • Providing a comparison table of different clustering quality measurement criteria • Applying dimension reduction methods and comparing the results of each one separately The data set used in this report is of tabular type and the information of different insurance policies is 1000 samples with 40 columns. Some of those columns are age, location of the incident, date of the incident, having a police report, etc.