Large Scale Hierarchical Classification: State of the Art

• Κύριοι συγγραφείς: Naik, Azad (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Rangwala, Huzefa (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: SpringerBriefs in Computer Science,
• Θέματα: Data mining.; Artificial intelligence.; Data Mining and Knowledge Discovery.; Artificial Intelligence.

This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state...

Πίνακας περιεχομένων:

• 1 Introduction
• 2 Background and Literature Review
• 3 Hierarchical Structure Inconsistencies
• 4 Large Scale Hierarchical Classification with Feature Selection
• 5 Multi-Task Learning
• 6 Conclusions and Future Research Directions.