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Performance Analysis of Dimensionality Reduction Techniques: Linear Vs. Non Linear
[摘要] 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.
[发布日期]  [发布机构] 
[效力级别]  [学科分类] 建筑学
[关键词] Dimension reduction;PCA;LDA;linear and non-linear techniques;software Engineering [时效性] 
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