Feature Selection and Dimensionality Reduction for Large Data set Clustering using Self-Organizing Maps

Abstract

Data mining is a form of analyzing the data which relates the newline techniques from fields like statistics machine learning databases artificial newline intelligence etc Clustering is one of the most important data mining newline techniques in which cluster of objects are grouped based on their similarity newline "Clustering is the process of accumulating the data records into considerable newline subclasses clusters in a way which enhances the relationship within clusters newline and reduces the similarity among two different clusters. The activity occurs every new academic year and schools with plenty of new students registered may feel a bit overwhelmed with this grouping assignment. A decision support system which can automatically perform grouping on a list of students may be able to help the school’s staffs with this repetitive task. A self-organizing map (SOM) is an example of unsupervised learning algorithm using an artificial neural network structure to produce a low dimensional representation from a given input.