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Evaluating the effect of unbalanced data in biomedical document classification
2011
Journal of Integrative Bioinformatics
SummaryNowadays, document classification has become an interesting research field. Partly, this is due to the increasing availability of biomedical information in digital form which is necessary to catalogue and organize. In this context, machine learning techniques are usually applied to text classification by using a general inductive process that automatically builds a text classifier from a set of pre-classified documents. Related with this domain, imbalanced data is a well-known problem in
doi:10.1515/jib-2011-177
fatcat:jwgqvt3k5naqbb4wb3ytjygequ