IT-Zeitschriften, Fachbücher, eBooks, digitale Magazine und vieles mehr - direkt im heise shop online kaufen
Warenkorb Ihr Warenkorb ist noch leer.

  •  
     
118,99 €*

Multilabel Classification

Problem Analysis, Metrics and Techniques
eBook

Bewerten Sie dieses Produkt als Erster

This book offers a comprehensive review of multilabel techniques widely used to classify and label texts, pictures, videos and music in the Internet. A deep review of the specialized literature on the field includes the available software needed to work with this kind of data. It provides the... > mehr
Sofortige Lieferung
Autor: Francisco Herrera, Francisco Charte, Antonio J. Rivera, María J. del Jesus
Anbieter: Springer
Sprache: Englisch
EAN: 9783319411118
Veröffentlicht: 09.08.2016
Format: PDF
Schutz: DRM Dieses eBook ist durch "Digital Rights Management" kurz DRM geschützt. Das bedeutet, dass Sie nach dem Kauf eines PDF-eBooks eine ACSM-Datei als Download erhalten. Sie benötigen für die Anzeige auf Ihrem Gerät die Software „Adobe Digital Editions“.
This book offers a comprehensive review of multilabel techniques widely used to classify and label texts, pictures, videos and music in the Internet. A deep review of the specialized literature on the field includes the available software needed to work with this kind of data. It provides the user with the software tools needed to deal with multilabel data, as well as step by step instruction on how to use them. The main topics covered are:

•The special characteristics of multi-labeled data and the metrics available to measure them.
•The importance of taking advantage of label correlations to improve the results.
•The different approaches followed to face multi-label classification.
•The preprocessing techniques applicable to multi-label datasets.
•The available software tools to work with multi-label data.

This book is beneficial for professionals and researchers in a variety of fields because of the wide range of potential applications for multilabel classification. Besides its multiple applications to classify different types of online information, it is also useful in many other areas, such as genomics and biology. No previous knowledge about the subject is required. The book introduces all the needed concepts to understand multilabel data characterization, treatment and evaluation.

Um bewerten zu können, melden Sie sich bitte an

  •