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With the rapid development of Internet, text categorization becomes a mission-critical technology that organizes and processes large amounts of data in document. Deep belief networks have powerful abilities of learning and can extract highly distinguishable features from the high-dimensional original feature space. So a new Chinese text categorization algorithm based on deep learning structure and...
This paper studies the imbalanced data classifycation problem and proposes bi-directional sampling based on clustering (BDSK) for the imbalanced data classification. This algorithm combines SMOTE over-sampling algorithm and under-sampling algorithm based on K-Means to solve the within-class imbalance problem and the between-class imbalance problem. It not only avoid induce too much noise but also...
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