
Multilabel Classification
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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.
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