Large Scale Hierarchical Classification: State of the Art

• Main Authors: Naik, Azad (Author, http://id.loc.gov/vocabulary/relators/aut), Rangwala, Huzefa (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: SpringerBriefs in Computer Science,
• Subjects: 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...

Table of Contents:

• 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.