Unsupervised Feature Extraction Applied to Bioinformatics

A PCA Based and TD Based Approach

Häftad, Engelska, 2025

Av Y-h. Taguchi, Y-H Taguchi

2 669 kr

Beställningsvara. Skickas inom 10-15 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (2)

Häftad

2 329 kr

Skickas inom 11-20 vardagar

Inbunden

3 329 kr

Skickas inom 7-10 vardagar

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 because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tensor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics.

Produktinformation

Utgivningsdatum2025-09-02
Mått155 x 235 x 30 mm
Vikt832 g
FormatHäftad
SpråkEngelska
SerieUnsupervised and Semi-Supervised Learning
Antal sidor533
Upplaga2
FörlagSpringer International Publishing AG
ISBN9783031609848

Tillhör följande kategorier

Biovetenskap inom Naturvetenskap och teknik
Elektronik och kommunikationer inom Naturvetenskap och teknik
Databaser inom Data och it
Systemvetenskap och AI inom Data och it
Algebra inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it

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.