A Novel Approach to Mathematical Concepts in Data Mining

This paper describes three different fundamental mathematical programming approaches that are relevant to data mining. They are: Feature Selection, Clustering and Robust Representation. This paper comprises of two clustering algorithms such as K-mean algorithm and K-median algorithms. Clustering is illustrated by the unsupervised learning of patterns and clusters that may exist in a given databases and useful tool for Knowledge Discovery in Database (KDD). The results of k-median algorithm are used to collecting the blood cancer patient from a medical database. K-mean clustering is a data mining/machine learning algorithm used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-mean algorithm is one of the simplest clustering techniques and it is commonly used in medical imaging, biometrics and related fields