classification labeled

Semi-Supervised Learning of Mixture Models

White Paper The authors show that unlabeled data can lead to an increase in classification error even in situations where additional labeled data would decrease classification error. This paper analyzes the performance of semi-supervised learning of mixture... [06 Nov 2007]

Learning From Labeled and Unlabeled Data on a Directed Graph

White Paper This paper proposes a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered. In the absence of labeled in-stances, this... [09 Jun 2007]

Combining Labeled and Unlabeled Data for Text Classification With a Large Number of Categories

White Paper A major difficulty with supervised learning techniques for text classification is that they often require a large number of labeled examples to learn accurately. This paper proposes a new algorithm aimed at combining the advantages that ECOC offers... [13 Apr 2005]

Wrapper Induction for End-User Semantic Content Development

White Paper These patterns allow users to overlay documents with RDF classes and properties, and then to interact with this labeled content within a larger Semantic Web application, such as Haystack. The transition from existing World Wide Web content to the... [23 Feb 2005]

Combining Labeled and Unlabeled Data for MultiClass Text Categorization

White Paper Supervised learning techniques for text classification often require a large number of labeled examples to learn accurately. Current text learning techniques for combining labeled and unlabeled, such as EM and Co-Training are mostly applicable for... [08 May 2004]

Effect of Unlabeled Data on Generative Classifiers, with Application to Model Selection

White Paper We then report on a large set of experiments involving labeled and unlabeled data, and demonstrate that unlabeled data can degrade classification performance when modeling assumptions are incorrect. We first characterize situations where unlabeled... [14 Aug 2003]

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