A comparison of self-organising maps and principal components analysis
Gopal Das
Indian Institute of Management Rohtak
Manojit Chattopadhyay and Sumeet Gupta
Indian Institute of Management Raipur
Introduction
The complexity of data in the higher dimensional space can be efficiently represented in the lower dimensional space using dimension reduction techniques (Choi 2014). Principal components analysis (PCA) and self-organising maps (SOM) are two of the most common approaches used for dimension reduction. PCA is an unsupervised approach to dimension reduction and is extensively applied to reduce the number of variables in a multivariate dataset to a smaller...