Data Editing Based Self-training Algorithm

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Provided by: Binary Information Press
Topic: Data Management
Format: PDF
Self-training algorithm is a semi-supervised classification algorithm which through repeated training with the labeled data to get a enlarged labeled data set and improve the classification accuracy meanwhile. Since the initial labeled data set in self-training algorithm may be small, a considerable number of data are mislabeled in the training process is unavoidable. A nearest neighbor rule based data editing technique is introduced, which extends traditional self-training algorithm by new methods of identifying and removing the mislabeled data, so that it can reduce the mislabeled data and improve the classification accuracy.
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