Factor Analysis Using Two Stages Neural Network Architecture

Factor Analysis is the process of finding a suitable representation of the data in terms of lesser number of variables. There are a number of application areas where factor analysis is widely used e.g. signal processing, statistics, stock marketing, forecasting, approximation, compression, security, medical sciences etc. In this paper we will show that a very effective factor analysis scheme can be developed using a feed forward neural network. Our approach has the advantage of being able to analyze very large data sets while preserving the nature of the data.

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