Unsupervised Feature Extraction Applied to Bioinformatics

A PCA Based and TD Based Approach

Éditeur :

Springer

Paru le : 2024-08-31

This updated book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case be...
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À propos

Auteur

Éditeur

Collection
n.c

Parution
2024-08-31

Pages
533 pages

EAN papier
9783031609817

Auteur(s) du livre


Prof. Taguchi is currently a Professor at Department of Physics, Chuo University. Prof. Taguchi received a master degree in Statistical Physics from Tokyo Institute of Technology, Japan in 1986, and PhD degree in Non-linear Physics from Tokyo Institute of Technology, Tokyo, Japan in 1988. He worked at Tokyo Institute of Technology and Chuo University. He is with Chuo University (Tokyo, Japan) since 1997. He currently holds the Professor position at this university. His main research interests are in the area of Bioinformatics, especially, multi-omics data analysis using linear algebra. Dr. Taguchi has published a book on bioinformatics, more than 150 journal papers, book chapters and papers in conference proceedings and was recognized as top 2% scientist of the world in 3rd consecutive years (2021, 2022, 2023) according to analysis of Stanford University, USA and report of Elsevier in bioinformatics.

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EAN PDF
9783031609824
Prix
168,79 €
Nombre pages copiables
5
Nombre pages imprimables
53
Taille du fichier
38717 Ko
EAN EPUB
9783031609824
Prix
168,79 €
Nombre pages copiables
5
Nombre pages imprimables
53
Taille du fichier
62966 Ko

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