Kernels for structured data

This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains....

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Gartner, Thomas
Format: E-Book Buch
Sprache:Englisch
Veröffentlicht: New Jersey World Scientific Publishing Co. Pte. Ltd 2008
World Scientific
World Scientific Publishing Company
WORLD SCIENTIFIC
World Scientific Publishing
Ausgabe:1
Schriftenreihe:Series in machine perception and artificial intelligence
Schlagworte:
Artificial Intelligence (Machine Learning, Neural Networks, Fuzzy Logic)
Computer Systems (Database Systems, Operating Systems)
Kernel functions
Machine learning
Robotics (Machine Vision, Pattern Recognition)
SCIENCE
Kernel Methods
Graph Kernels
Machine Learning
Relational Learning
Structured Data
ISBN:9812814558, 9789812814555, 9789812814562, 9812814566
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.
Bibliographie:Includes bibliographical references (p. 179-190) and index
ISBN:9812814558
9789812814555
9789812814562
9812814566
DOI:10.1142/6855