New modification version of principal component analysis with kinetic correlation matrix using kinetic energy

Principle Component Analysis (PCA) is a direct, non-parametric method for extracting pertinent information from confusing data sets. It presents a roadmap for how to reduce a complex data set to a lower dimension to disclose the hidden, simplified structures that often underlie it. However, most PCA...

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Bibliographic Details
Main Authors: Sara Al-Ruzeiqi, Christian Dawson
Format: Default Conference proceeding
Published: 2018
Subjects:
Other information and computing sciences not elsewhere classified
Principle Component Analysis (PCA)
Kinetic correlation matrix
Kinetic energy
Algorithm
Prediction
Information and Computing Sciences not elsewhere classified
Online Access:https://hdl.handle.net/2134/33405
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