Téléchargez le livre : Large Scale Hierarchical Classification: State of the Art

Large Scale Hierarchical Classification: State of the Art

de

,

Éditeur :

Springer


Collection :

SpringerBriefs in Computer Science

Paru le : 2018-10-09

eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
52,74 €
Téléchargement immédiat
Dès validation de votre commande
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description

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.
Pages
93 pages
Collection
SpringerBriefs in Computer Science
Parution
2018-10-09
Marque
Springer
EAN papier
9783030016197
EAN PDF
9783030016203
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
9
Taille du fichier
3973 Ko
Prix
52,74 €
EAN EPUB
9783030016203
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
9
Taille du fichier
20419 Ko
Prix
52,74 €

Suggestions personnalisées