Download or read book Large Scale Hierarchical Classification written by Azad Naik and published by . This book was released on 2018 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by LSHC is discussed in detail such as: 1. High imbalance between classes at different levels of the hierarchy; 2. Incorporating relationships during model learning leads to optimization issues; 3. Feature selection; 4. Scalability due to large number of examples, features and classes; 5. Hierarchical inconsistencies; 6. Error propagation due to multiple decisions involved in making predictions for top-down methods. The brief also demonstrates how multiple hierarchies can be leveraged for improving the HC performance using different Multi-Task Learning (MTL) frameworks.