What is it about?
It is feature extraction based upon tensor decomposition, which was extended from the recently proposed principal component analysis based unsupervised feature extraction.
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Why is it important?
It can be used for multi-view data analysis by generating tensor from the product of matrix. Generated tensor was decomposed by the usual tensor decomposition method.
Perspectives
As a bioinformatics researcher, I am happy that PCA based unsupervised FE was extended to tensor decompsoition.
Professor Y-h. Taguchi
Chuo Daigaku
Read the Original
This page is a summary of: Tensor decomposition-based unsupervised feature extraction applied to matrix products for multi-view data processing, PLoS ONE, August 2017, PLOS,
DOI: 10.1371/journal.pone.0183933.
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Resources
テンソル分解を用いた教師なし学習による変数選択
Japanese presentation at http://ainow.ai/2017/08/28/120881/
テンソル分解を用いた教師なし学習による変数選択
presentation
Tensor decomposition based unsupervised feature extraction applied to matrix products for multiview data processing
Presentation at AYRCOB2017 http://2017.ayrcob.org 31th Oct 2017, Seoul, Korea
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