Multi-Label Dimensionality Reduction Multi-Label Dimensionality Reduction
Chapman & Hall/CRC Machine Learning & Pattern Recognition

Multi-Label Dimensionality Reduction

Liang Sun and Others
    • 64,99 €
    • 64,99 €

Publisher 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

GENRE
Business & Personal Finance
RELEASED
2016
19 April
LANGUAGE
EN
English
LENGTH
208
Pages
PUBLISHER
CRC Press
SIZE
4.6
MB
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