A STUDY ON DIMENSION REDUCING COMPONENTS FOR MULTIVARIATE DATA
NADIA ELBAHLUL ELGREGNI;
Abstract
The central idea of principal component analysis is to reduce the dimensionality of a data set, in which there is a large number of interrelated variables, while retaining as much as possible of its variation. This reduction is achieved by transforming th
Other data
| Title | A STUDY ON DIMENSION REDUCING COMPONENTS FOR MULTIVARIATE DATA | Other Titles | دراسة حول تقليل أبعاد مكونات بيانات متعددة المتغيرات | Authors | NADIA ELBAHLUL ELGREGNI | Keywords | A STUDY ON DIMENSION REDUCING COMPONENTS FOR MULTIVARIATE DATA | Issue Date | 2010 | Description | The central idea of principal component analysis is to reduce the dimensionality of a data set, in which there is a large number of interrelated variables, while retaining as much as possible of its variation. This reduction is achieved by transforming th |
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| File | Size | Format | |
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| 99678p1311.pdf | 84.69 kB | Adobe PDF | View/Open |
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