
Compression Schemes for Mining Large Datasets
a machine learning perspective
$210.02
- Paperback
197 pages
- Release Date
17 September 2016
Summary
This book addresses the challenges of data abstraction generation using a least number of database scans, compressing data through novel lossy and non-lossy schemes, and carrying out clustering and classification directly in the compressed domain. Schemes are presented which are shown to be efficient both in terms of space and time, while simultaneously providing the same or better classification accuracy. Features: describes a non-lossy compression scheme based on run-length encoding of patt…
Book Details
| ISBN-13: | 9781447170556 |
|---|---|
| ISBN-10: | 1447170555 |
| Author: | M. Narasimha Murty, S.V. Subrahmanya, T. Ravindra Babu |
| Publisher: | Springer London Ltd |
| Imprint: | Springer London Ltd |
| Format: | Paperback |
| Number of Pages: | 197 |
| Release Date: | 17 September 2016 |
| Weight: | 3.34kg |
| Dimensions: | 235mm x 155mm |
| Series: | Advances in Computer Vision and Pattern Recognition |
About The Author
M. Narasimha Murty
Dr. T. Ravindra Babu is a Principal Researcher in the E-Commerce Research Labs at Infosys Ltd., Bangalore, India. Mr. S.V. Subrahmanya is Vice President and Research Fellow at the same organization. Dr. M. Narasimha Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore, India.
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