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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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Bibliografische gegevens
Gepubliceerd in:J Comput Graph Stat
Hoofdauteurs: Guo, Ruixin, Ahn, Mihye, Zhu, Hongtu
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2014
Onderwerpen:
Online toegang: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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