Francisco Herrera Francisco Charte Antonio J. Rivera María J. del Jesus Herrera Multilabel Classification

Multilabel Classification

von Francisco Herrera Francisco Charte Antonio J. Rivera María J. del Jesus

Problem Analysis, Metrics and Techniques

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Beschreibung

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.

Covers key concepts of multilabel data characterization, treatment, and evaluation Equips the reader with all the software tools needed to handle multilabel data, including step-by-step instructions for use Provides the perfect guide for beginners and practitioners with interest in the topic, as well as experts seeking a comprehensive overview Includes supplementary material: sn.pub/extras

Autor*in

Francisco Herrera

Themen in »Multilabel Classification«

Data mining Machine learning Classification Multi-label data Text categorization Preprocessing Dataset characterization Learning from imbalanced data Dimensionality reduction Feature selection Data mining software

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Details

ISBN: 9783319822693
Verlag: Springer International Publishing
Erscheinung: 22.04.2018

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