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Adversarial pattern classification has been proposed in. In adversarial pattern classification, an adversary wants to change the attributes of an instance to let the classifier make a wrong classification to gain utility. But to disguise an instance an adversary has to pay a cost. The adversary will never do this if the cost is higher than the utility. Adversarial classification systems include examples...
For the virtues such as simplicity, high generalization capability, and few training cost, the K-Nearest-Neighbor (KNN) classifier is widely used in pattern recognition and machine learning. However, the computation complexity of KNN classifier will become higher when dealing with large data sets classification problem. In consequence, its efficiency will be decreased greatly. This paper proposes...
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