
handle: 10525/2387
Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014 Recently, there has been significant interest in multi-dimensional representation of the objects, searching for new features in new sources of information. Each view of the object represents a separate data source for learning a separate classifier. A multi-view teaching algorithm is compared to a single learner. Both models use Naïve Bayes Classifier for the underlying classifiers. The multi-view algorithm is especially applicable in areas where it is difficult to obtain the classifications of the examples. Association for the Development of the Information Society, Institute of Mathematics and Informatics Bulgarian Academy of Sciences, Plovdiv University "Paisii Hilendarski"
semi-supervised learning, classification, co-training
semi-supervised learning, classification, co-training
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