Implementation of K-Means Clustering Algorithm in the Crime Data Set

Data mining is a most promising field to group the relative set of data. The data mining deals with many algorithms to discover interesting and useful pattern or to find new knowledge form the dataset. Clustering is the technique of grouping the dynamic data in to classes. K-.Means Clustering algorithms is one of the efficient clustering algorithm. In Data mining processing work, The first step include to collect raw data and process with key factors and to determine which algorithms is more suitable for the given data set. Criminology is the study of   identifying the crime characteristics. This paper gives an idea about implementation of K-means Algorithms for crime data set. It also takes part of crime analysis the exploration and finding crimes with criminals. The volume and complexity and their relationships of crime database is the challenge attributes. This will paper intended to create effective tool for police forces.