Sarveniazi, Alireza (2014) An Actual Survey of Dimensionality Reduction. American Journal of Computational Mathematics, 04 (02). pp. 55-72. ISSN 2161-1203
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Official URL: https://doi.org/10.4236/ajcm.2014.42006
Abstract
Dimension reduction is defined as the processes of projecting high-dimensional data to a much lower-dimensional space. Dimension reduction methods variously applied in regression, classification, feature analysis and visualization. In this paper, we review in details the last and most new version of methods that extensively developed in the past decade.
Item Type: | Article |
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Subjects: | STM Academic > Mathematical Science |
Depositing User: | Unnamed user with email support@stmacademic.com |
Date Deposited: | 17 Jun 2023 09:48 |
Last Modified: | 23 Jan 2024 04:42 |
URI: | http://article.researchpromo.com/id/eprint/1100 |