Name: Unsupervised Feature Extraction Applied to Bioinformatics. A PCA Based and TD Based Approach
SKU: 64792286
Price: 154.55 EUR
Availability: InStock
Author: Y-h. Taguchi
ISBN: 9783031609848

portada Unsupervised Feature Extraction Applied to Bioinformatics. A PCA Based and TD Based Approach

Unsupervised Feature Extraction Applied to Bioinformatics. A PCA Based and TD Based Approach

Type

Physical Book

Publisher

Springer International Publishing AG

Author

Y-h. Taguchi

Collection

Unsupervised and Semi-Supervised Learning

Year

2025

Pages

533

Format

Paperback

Dimensions

23.5x15.5 cm

ISBN13

9783031609848

Unsupervised Feature Extraction Applied to Bioinformatics. A PCA Based and TD Based Approach

Y-H. Taguchi (Author) · Springer International Publishing AG · Paperback

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Synopsis "Unsupervised Feature Extraction Applied to Bioinformatics. A PCA Based and TD Based Approach"

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.