منابع مشابه
Multi-interval Discretization of Continuous Attributes for Label Ranking
Label Ranking (LR) problems, such as predicting rankings of financial analysts, are becoming increasingly important in data mining. While there has been a significant amount of work on the development of learning algorithms for LR in recent years, preprocessing methods for LR are still very scarce. However, some methods, like Naive Bayes for LR and APRIORI-LR, cannot deal with real-valued data ...
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A large body of research in supervised learning deals with the analysis of singlelabel data, where training examples are associated with a single label λ from a set of disjoint labels L. However, training examples in several application domains are often associated with a set of labels Y ⊆ L. Such data are called multi-label. Textual data, such as documents and web pages, are frequently annotat...
متن کاملMulti-Label classification for Mining Big Data
In big data problems mining requires special handling of the problem under investigation to achieve accuracy and speed on the same time. In this research we investigate the multi-label classification problems for better accuracy in a timely fashion. Label dependencies are the biggest influencing factor on performance, directly and indirectly, and is a distinguishing factor for multi-label from ...
متن کاملActive Learning Algorithms for Multi-label Data
The iterative supervised learning setting, in which learning algorithms can actively query an oracle for labels, e.g. a human annotator that understands the nature of the problem, is called active learning. As the learner is allowed to interactively choose the data from which it learns, it is expected that the learner would perform better with less training. The active learning approach is appr...
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We report on a probabilistic approach for the classification of chronically ill patients. We rely on multi-label learning for its ability to represent in a natural way classification problems involving coexistence of diseases. We use a public clinical database for the evaluation of our proposed algorithm. Preliminary results show the benefits of our approach.
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ژورنال
عنوان ژورنال: Information Sciences
سال: 2016
ISSN: 0020-0255
DOI: 10.1016/j.ins.2015.10.032