Group-Wise Principal Component Analysis for Exploratory Data Analysis

In this article, we propose a new framework for matrix factorization based on principal component analysis (PCA) where sparsity is imposed. The structure to impose sparsity is defined in terms of groups of correlated variables found in correlation matrices or maps. The framework is based on three ne...

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Veröffentlicht in:	Journal of computational and graphical statistics 2017-07, Vol.26 (3), p.501-512
Hauptverfasser:	Camacho, José, Rodríguez-Gómez, Rafael A., Saccenti, Edoardo
Format:	Artikel
Sprache:	eng
Schlagworte:	Correlation Data analysis Exploratory data analysis Exploratory Data Analysis, Missing-Data, Sparsity, Matrix Factorization, Visualization Factorization Matrix Matrix factorization Missing-data Principal components analysis Sparsity Statistical Graphics Studies Visualization
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