A Semi-Supervised Framework for MMMs-Induced Fuzzy Co-Clustering with Virtual Samples
Although the goal of clustering is to reveal structural information from unlabeled datasets, in cases with partial structural supervisions, semi-supervised clustering is expected to improve partition quality. However, in many real applications, it may cause additional costs to provide an enough amou...
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Main Authors: | Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu |
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Format: | Article |
Language: | English |
Published: |
Wiley
2016-01-01
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Series: | Advances in Fuzzy Systems |
Online Access: | http://dx.doi.org/10.1155/2016/5206048 |
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