Performance Analysis of Dimensionality Reduction Techniques: Linear Vs. Non Linear

Anuradha Dhull, Yogita Gigras, Kavita Choudhary, Pratibha Kadian

Abstract


Dimension reduction is one of the important techniques used for projecting high dimensional data to a comparative lower dimensional space. Reduction techniques are basically applied in various domains like regression, classification and the feature analysis of given dataset. This paper provides a comprehensive look on different dimensionality techniques applied on high dimensional data to perform the reduction. A brief comparison among various linear and non linear techniques on some effective parameters is also discussed in this paper. In short, this paper will be a good startup for the beginners interested in doing research in the dimensionality reduction techniques.

Keywords


Dimension reduction; PCA; LDA; linear and non-linear techniques; software Engineering

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