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Clustering in high dimensional data is an important task. Subspace clustering has emerged as a possible solution to the challenges associated with high dimensional clustering. A subspace cluster is a subset of points together with a subset of attributes, such that some category of value of cluster points has great aggregation in these attributes. This paper proposes a subspace clustering algorithm...
With the explosive growth and extensive applications of spatial data sets, it is becoming more and more important to solve the problem how to discover knowledge automatically from spatial data sets. Co-location patterns discovery is an important branch in spatial data mining. Traditional algorithms for co-location patterns mining can only find positive co-location patterns. However, negative co-location...
Software fault prediction models play an important role in software quality assurance. They identify software subsystems (modules,components, classes, or files) which are likely to contain faults. These subsystems, in turn, receive additional resources for verification and validation activities. Fault prediction models are binary classifiers typically developed using one of the supervised learning...
Surface fluorination and oxyfluorination were performed for LLDPE to suppress the charge injection under HVDC. The astonishing suppression effects are obtained especially by the oxyfluorination and also by the industrial fluorination, as observed by the measurements of space charge profile based on the PWP method. However, considerably different cases of space charge profile are seen between the laboratory...
Classification is important in data mining. In this paper, a multiple evolutionary neural network classifier based on niche genetic algorithm (MNC-NG) is presented, which establishes classifiers by a group of three-layer feed-forward neural networks with high accuracy and good diversity. The neural networks are trained by niche genetic algorithm based on clustering. The class label of the identifying...
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