Performing Age Group Clustering in Breast Cancer Datasets Using FCM Algorithm

The goal of clustering is to group and distinguish comparable units and to separate them from differing units. Classifying patients into groups is not a new phenomenon. It is a concept that, although not always recognized as such, dates back to the beginning of medical science .In fact, it can be said that the idea is based on the notion of a search for a natural ordering of things, which is a basic characteristic of human beings. Fairly recent additions to this concept, however, are 1) the wide-scale application of clustering and classification techniques to patients intra- and inter institutionally for determining medical resource utilization and 2) the growing importance being attached to the reliability and validity aspects of classification procedures and the resulting schemes in general.3) Certain critical decisions must be made in order to properly utilize cluster analysis. Towards this end, cluster analysis encompasses a wide range of statistical techniques. In this paper from the large number of database the retrieved information can have the details of person who are affected by breast cancer. Using those breast cancer datasets performs 1) information retrieval is based on the specified region. That retrieving breast cancer details from the selected database. 2) Clustering the breast cancer details based on age group.