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Positive and unlabeled learning (PU Learning) is a special semi-supervise learning method. Its most important feature is that training set only includes two parts: positive examples and unlabeled examples. Many real-world classification applications appeal to PU Learning problem. The K-means++ clustering algorithm proposed a new seeding method. This paper describes a semi-supervised learning algorithm...
This paper adopts the mixed neural network to forecast the railway freight volume. It determines the characteristic parameters and the number of the neurons of input layer and hidden layer based on the freight volume previously. Finally this paper establishes a model of mixed neural network to forecast the railway freight volume.
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