Multi-Label Dimensionality Reduction by Liang Sun, Shuiwang Ji and Jieping Ye
English | 2013 | ISBN: 1439806152 | 208 pages | PDF | 3 MB
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.