Multilabel Classification

Problem Analysis, Metrics and Techniques
Buch | Hardcover
XVI, 194 Seiten
2016 | 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-41110-1 (ISBN)

Lese- und Medienproben

Multilabel Classification - Francisco Herrera, Francisco Charte, Antonio J. Rivera, María J. del Jesus
106,99 inkl. MwSt
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.

Introduction.- Multilabel Classification.- Case Studies and Metrics.- Transformation based Classifiers.- Adaptation based Classifiers.- Ensemble based Classifiers.- Dimensionality Reduction.- Imbalance in Multilabel Datasets.- Multilabel Software.

Erscheinungsdatum
Zusatzinfo XVI, 194 p. 72 illus.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte artificial intelligence (incl. robotics) • classification • Computer Science • Data Mining • data mining and knowledge discovery • Data mining software • Dataset characterization • dimensionality reduction • Feature Selection • Learning from imbalanced data • machine learning • Multi-label data • Preprocessing • text categorization
ISBN-10 3-319-41110-1 / 3319411101
ISBN-13 978-3-319-41110-1 / 9783319411101
Zustand Neuware
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