4578 search results - page 434 / 916 » Learning from Multi-source Data |
135
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CIDM
2009
IEEE
15 years 11 months ago
2009
IEEE
— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
132
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GFKL
2007
Springer
15 years 10 months ago
2007
Springer
Abstract. A central task when integrating data from different sources is to detect identical items. For example, price comparison websites have to identify offers for identical p...
143
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SDM
2008
SIAM
15 years 6 months ago
2008
SIAM
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
125
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CSCW
2002
ACM
15 years 4 months ago
2002
ACM
Mobile technology requires new methods for studying its use under realistic conditions "in the field." Reflexively, mobile technology also creates new opportunities for ...
151
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MICAI
2010
Springer
2010
Springer
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
15 years 2 months ago
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...