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We propose a novel algorithm based on clustering to extract rules from artificial neural networks. After networks Beijing trained and pruned successfully, inner-rules are generated by discrete activation values of hidden units. Then, weights between input and hidden units are clustered to decrease the complexity of rules extraction. In clustering phase, the clustered number of weights can be adjusted...
Based on an analysis on the Web log mining algorithm of predecessors, this paper presents the Web site structure optimization technology to improve customer interest. The technology proposes similar customer groups and clustering algorithms of relevant Web pages based on interest matrix of customers accessing a Web site to discover the hidden customer access patterns. Experiment results demonstrate...
DNA splice site adjacent sequences have remarkable conservative feature, and mining their underlying biological knowledge has become a key issue in the field of DNA sequences analysis. In this paper, we analyze the feature of human beingpsilas DNA splice site adjacent sequences. Firstly, we propose a kind of DNA splice site sequences clustering method based on Genetic K-modes; secondly, we analyze...
K-means algorithm is widely used in spatial clustering. It takes the mean value of each cluster centroid as the Heuristic information, so it has some disadvantages: sensitive to the initial centroid and instability. The improved clustering algorithm referred to the best clustering centriod which is searched during the optimization of clustering centroid. That increased the searching probability around...
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