Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

Large Scale Hierarchical Classification: State of the Art

by Azad Naik
Save 35% Save 35%
Current price ₹3,672.00
Original price ₹5,649.00
Original price ₹5,649.00
Original price ₹5,649.00
(-35%)
₹3,672.00
Current price ₹3,672.00

Imported Edition - Ships in 12-14 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Paperback
  • ISBN13: 9783030016197
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 93
  • Original Price: EUR 49.99
  • Language: English
  • Edition: 2018
  • Item Weight: 181 grams
  • BISAC Subject(s): Data Science / Data Analytics, Artificial Intelligence / General, and Probability & Statistics / General

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 forimproving the HC performance using different Multi-Task Learning (MTL) frameworks.

The purpose of this book is two-fold:

1. Help novice researchers/beginners to get up to speed by providing a comprehensive overview of several existing techniques.

2. Provide several research directions that have not yet been explored extensively to advance the research boundaries in HC.

New approaches discussed in this book include detailed information corresponding to the hierarchical inconsistencies, multi-task learning and feature selection for HC. Its results are highly competitive with the state-of-the-art approaches in the literature.


Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us