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Traditional online learning algorithms are designed for vector data only, which assume that the labels of all the training examples are provided. In this paper, we study graph classification where only limited nodes are chosen for labelling by selective sampling. Particularly, we first adapt a spectral-based graph regularization technique to derive a novel online learning linear algorithm which can...
Active learning is a hot topic in machine learning field. The main task of active learning is to automatically select the representative instances for efficiently reducing the sample complexity. This paper presents a brief survey of active learning regarding selection methods, query strategies, applications and other related works.
Grade estimation is one of the most complicated aspects in mining. Its complexity originates from scientific uncertainty. In this paper, a fuzzy wavelet neural network (FWNN) is proposed for grade estimation. This fuzzy neural network uses wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability. The new FWNN method...
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