Multi-Label Dimensionality Reduction Hardback
by Liang Sun, Shuiwang Ji, Jieping Ye
Part of the Chapman & Hall/CRC Machine Learning & Pattern Recognition series
Hardback
Description
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 a unified treatment of multi-label dimensionality reduction that incorporates both algorithmic developments and applications.
Addressing this shortfall, Multi-Label Dimensionality Reduction covers the methodological developments, theoretical properties, computational aspects, and applications of many multi-label dimensionality reduction algorithms.
It explores numerous research questions, including: How to fully exploit label correlations for effective dimensionality reductionHow to scale dimensionality reduction algorithms to large-scale problemsHow to effectively combine dimensionality reduction with classificationHow to derive sparse dimensionality reduction algorithms to enhance model interpretabilityHow to perform multi-label dimensionality reduction effectively in practical applicationsThe authors emphasize their extensive work on dimensionality reduction for multi-label learning.
Using a case study of Drosophila gene expression pattern image annotation, they demonstrate how to apply multi-label dimensionality reduction algorithms to solve real-world problems.
A supplementary website provides a MATLAB® package for implementing popular dimensionality reduction algorithms.
Information
-
Out of stock
- Format:Hardback
- Pages:208 pages, 14 Tables, black and white; 23 Illustrations, black and white
- Publisher:Taylor & Francis Inc
- Publication Date:04/11/2013
- Category:
- ISBN:9781439806159
Other Formats
- PDF from £39.68
Information
-
Out of stock
- Format:Hardback
- Pages:208 pages, 14 Tables, black and white; 23 Illustrations, black and white
- Publisher:Taylor & Francis Inc
- Publication Date:04/11/2013
- Category:
- ISBN:9781439806159
