Compression Schemes for Mining Large Datasets is popular PDF and ePub book, written by T. Ravindra Babu in 2013-11-19, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Compression Schemes for Mining Large Datasets can be Read Online from any device for your convenience.
Compression Schemes for Mining Large Datasets Book PDF 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 patterns with binary valued features; proposes a lossy compression scheme that recognizes a pattern as a sequence of features and identifying subsequences; examines whether the identification of prototypes and features can be achieved simultaneously through lossy compression and efficient clustering; discusses ways to make use of domain knowledge in generating abstraction; reviews optimal prototype selection using genetic algorithms; suggests possible ways of dealing with big data problems using multiagent systems.
Detail Book of Compression Schemes for Mining Large Datasets PDF
- Author : T. Ravindra Babu
- Release : 19 November 2013
- Publisher : Springer Science & Business Media
- ISBN : 9781447156079
- Genre : Computers
- Total Page : 208 pages
- Language : English
- PDF File Size : 13,8 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Compression Schemes for Mining Large Datasets by T. Ravindra Babu, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.