Multi-Label Dimensionality Reduction (1) (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
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- Synopsis
- Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality. An effective way to mitigate this problem is through dimensionality reduction, which extracts a small number of features by removing irrelevant, redundant, and noisy information. The data mining and machine learning literature currently lacks
- Copyright:
- 2014
Book Details
- Book Quality:
- Publisher Quality
- Book Size:
- 208 Pages
- ISBN-13:
- 9781040069875
- Related ISBNs:
- 9781439806166, 9781439806159, 9780429148200
- Publisher:
- CRC Press
- Date of Addition:
- 01/26/25
- Copyrighted By:
- Taylor & Francis Group, LLC
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Business and Finance, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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