Unsupervised Feature Extraction Applied to Bioinformatics (Record no. 75825)
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| 000 -LEADER | |
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| fixed length control field | 03699nam a22006015i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-22456-1 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801214001.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 190823s2020 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783030224561 |
| -- | 978-3-030-22456-1 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 621.382 |
| 100 1# - AUTHOR NAME | |
| Author | Taguchi, Y-h. |
| 245 10 - TITLE STATEMENT | |
| Title | Unsupervised Feature Extraction Applied to Bioinformatics |
| Sub Title | A PCA Based and TD Based Approach / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XVIII, 321 p. 111 illus., 94 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Unsupervised and Semi-Supervised Learning, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction to linear algebra -- Matrix factorization -- Tensor decompositions -- PCA based unsupervised FE -- TD based unsupervised FE -- Application of PCA/TD based unsupervised FE to bioinformatics -- Application of TD based unsupervised FE to bioinformatics. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-030-22456-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2020. |
| 336 ## - | |
| -- | text |
| -- | txt |
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| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Telecommunication. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Signal processing. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern recognition systems. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Communications Engineering, Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational and Systems Biology. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Signal, Speech and Image Processing . |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Automated Pattern Recognition. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2522-8498 |
| 912 ## - | |
| -- | ZDB-2-ENG |
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| -- | ZDB-2-SXE |
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