Mining Customer’s Data for Vehicle Insurance Prediction System using k-Means Clustering - An Application

Data mining or mining customer’s data helps to discover the key characteristics from the customer’s data, and possibly use those characteristics for future prediction. The problem of selecting the “best” algorithm/parameter setting is a difficult one. However kMeans Clustering is an algorithm helps to classify or to group the objects based on attributes/features into k number of groups. A good clustering algorithm ideally should produce groups with distinct non-overlapping boundaries, although a perfect separation cannot typically be achieved in practice. In this paper, an approach has been made by collecting data samples from customers, and then applying clustering on optimized data for Vehicle Insurance Prediction System. To determine which algorithm is good is a function of the type of data available and the particular purpose of analysis. KeywordsData Mining, Vehicle Insurance, k – Means Clustering, Prediction, databases.