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E-learning behavior analysis is an important issue to the instruction based on Internet. This paper proposed a new method to analyze the e-learning behavior. It classified e-learning behaviors into several clusters by fuzzy clustering algorithm. Behaviors in the same cluster have the most common in characters, while behaviors between clusters have the least common. Experiments fully demonstrated that...
In practical issues, categorical data and numerical data usually coexist, and a unified data reduction technique for hybrid data is desirable. In this paper, an information measure is proposed for computing the discernibility power of a categorical or numeric attribute. Based on the measure, a uniform definition of significance of attributes with categorical values and numerical values is proposed...
In this paper, we propose a new method of designing and constructing ldquogoodrdquo mappings defined by kernel functions for classification task, called Optimal Successive Mappings (OSM). Kernel methods, such as Support Vector Machines (SVM), could not provide satisfactory classification accuracy on some complicated data sets, which are still not linearly separable in feature space. It means kernels...
Differential evolution (DE) and particle swarm optimization (PSO) are the evolutionary computation paradigms, and both have shown superior performance on complex nonlinear function optimization problems. This paper detects the underlying relationship between them and then qualitatively proves that the two heuristic approaches from different theoretical background are consistent in form. Within the...
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