Analyzing the Effectiveness and Applicability of Co-training

Abstract

Recently there has been signi cant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applies to datasets that have a natural separation of their features into two disjoint sets. We demonstrate that when learning from labeled and unlabeled data, algorithms explicitly… (More)
DOI: 10.1145/354756.354805

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