A comparison of self-organising maps and principal components analysis

This paper attempts to compare self-organising maps (SOM) and principal components analysis (CPA) by applying them to the marketing construct 'retail store personality'.
Das et al.

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...

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