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Spatially Weighted Principal Component Analysis for Imaging Classification

The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex...

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Bibliografski detalji
Izdano u:J Comput Graph Stat
Glavni autori: Guo, Ruixin, Ahn, Mihye, Zhu, Hongtu
Format: Artigo
Jezik:Inglês
Izdano: 2014
Teme:
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC4467033/
https://ncbi.nlm.nih.gov/pubmed/26089629
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/10618600.2014.912135
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