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This paper proposes a new multiple instance learning (MIL) method based on a MIL back-propagation neural network (MIBP), which is an extension of the standard back-propagation neural network (BPNN) that uses labeled bags of instances as training data. The method finds a concept point t in the feature space which is close to instances from positive bags and far from instances in negative bags. Our...
This paper proposes a new email classification model using a linear neural network trained by perceptron learning algorithm (PLA) and a nonlinear neural network trained by back propagation neural network (BPNN). A semantic feature space (SFS) method has been introduced in this classification model. The bag of word based email classification system has the problems of large number of features and ambiguity...
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