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In this paper we investigate experimentally how different sources of uncertainty affect the classification performance of an SVM based binary classifier. Our aim is to find statistically sound methods for controlling the detrimental effects of such sources when a classifier is to be implemented in hardware platforms where severe limitations force designers to allocate power, computation and memory...
In this paper we investigate experimentally how different sources of uncertainty affect the classification performance of an SVM based binary classifier. Our aim is to find statistically sound methods for controlling the detrimental effects of such sources when a classifier is to be implemented in hardware platforms where severe limitations force designers to allocate power, computation and memory...
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