Abstract
Rare category analysis is related to many research areas, including active learning, where the goal is to improve the classification performance with the fewest label requests to the labeling oracle; imbalanced classification, where the goal is to construct a classifier for imbalanced data sets which is able to identify the under represented classes; anomaly detection (outlier detection), which refers to the problem of finding patterns in the data that do not conform to expected behavior; clustering, which refers to the problem of grouping similar data items into clusters; co-clustering, which generally involves grouping the data from various dimensions; and unsupervised feature selection, where the goal is to select features for the sake of grouping the data without any supervision.
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© 2011 Springer-Verlag Berlin Heidelberg
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He, J. (2011). Survey and Overview. In: Analysis of Rare Categories. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22813-1_2
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DOI: https://doi.org/10.1007/978-3-642-22813-1_2
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-22813-1
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