Name: Unsupervised Feature Extraction Applied to Bioinformatics: A Pca Based and TD Based Approach (en Inglés)
Price: 3996.83 MXN
Availability: InStock
Author: Taguchi, Y-H
ISBN: 9783030224585

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portada Unsupervised Feature Extraction Applied to Bioinformatics: A Pca Based and TD Based Approach (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Taguchi, Y-H

Idioma

Inglés

N° páginas

321

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.8 cm

Peso

0.48 kg.

ISBN13

9783030224585

Categorías

Anatomía
Fisiologiía
Biología
Ingeniería de las comunicaciones y las telecomunicaciones
Ciencias de la computación

Unsupervised Feature Extraction Applied to Bioinformatics: A Pca Based and TD Based Approach (en Inglés)

Taguchi, Y-H (Autor) · Springer · Tapa Blanda

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Unsupervised Feature Extraction Applied to Bioinformatics: A Pca Based and TD Based Approach (en Inglés)"

This 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 tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features;Provides a fast algorithm, based upon linear algebra, to analyze big data;Includes several applications to multi-view data analyses, with a focus on bioinformatics.