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Learning from positive and unlabeled examples (PU learning) has been a hot topic for classification in machine learning. The key feature of this problem is that there is no labeled negative training data, which makes the traditional classification techniques inapplicable. According to this feature, we propose an algorithm called biased locality-sensitive support vector machine based on density (BLSBD-SVM)...
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