Read While You Wait - Get immediate ebook access, if available*, when you order a print book

Springer Theses

Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings

Authors: T. Pham, Thuy

Free Preview
  • Nominated as an outstanding PhD thesis by The University of Sydney, Australia
  • Reports on an improved feature selection technique based on voting
  • Offers a comprehensive review of machine learning methods for unsupervised classification and feature selection
see more benefits

Buy this book

eBook 96,29 €
price for Spain (gross)
  • ISBN 978-3-319-98675-3
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-319-98674-6
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-030-07518-7
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.


Table of contents (7 chapters)

Table of contents (7 chapters)

Buy this book

eBook 96,29 €
price for Spain (gross)
  • ISBN 978-3-319-98675-3
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-319-98674-6
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-030-07518-7
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings
Authors
Series Title
Springer Theses
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-319-98675-3
DOI
10.1007/978-3-319-98675-3
Hardcover ISBN
978-3-319-98674-6
Softcover ISBN
978-3-030-07518-7
Series ISSN
2190-5053
Edition Number
1
Number of Pages
XV, 107
Number of Illustrations
3 b/w illustrations, 32 illustrations in colour
Topics

*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works and instructor copies are not included.