Applied Biclustering Methods for Big and High-Dimensional Data Using R (1) (Chapman & Hall/CRC Biostatistics Series)

By: Adetayo Kasim and Ziv Shkedy and Sebastian Kaiser and Sepp Hochreiter and Willem Talloen

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix.The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

Book Quality:: Publisher Quality
Book Size:: 428 Pages
ISBN-13:: 9781315356396
Related ISBNs:: 9781482208238, 9781315373966, 9780367736859, 9781315337333, 9781482208245
Publisher:: CRC Press
Date of Addition:: 04/03/25
Copyrighted By:: Taylor & Francis Group, LLC
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: null Adetayo Kasim
Edited by:: null Ziv Shkedy
Edited by:: null Sebastian Kaiser
Edited by:: null Sepp Hochreiter
Edited by:: null Willem Talloen