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Multi-label classification in social network environments is becoming a key area of data mining research in recent years. Given some nodes' labels (i.e., the sources), the task is to infer some other nodes' labels (i.e., the targets) in the same network. Relational classification methods, which leverage the correlation of labels between linked instances, have been shown to outperform traditional classifiers...
The Discrete Particle Swarm Optimization (DPSO) has little parameters and high convergent capability of the global optimizing. Based on the existing PSO-based classification system we constructed a new classification system based on Discrete PSO. We used the variable-length method to represent particle in the process of operation, represent rule set in a reasonable way and do some appropriate cut,...
The standard causal discovery assumes that all variables are available from the beginning. In this paper, we consider an untouched scenario in which not all variables are available in advance. We call this scenario online causal discovery which assumes that the target of interest is given in advance while the other variables are unknown. With this situation, an online algorithm is presented which...
Fuzzy Kohonen clustering networks (FKCN) are well known for clustering analysis (unsupervised learning and self-organizing). This classification of FKCN algorithm is a set of iterative procedures that suffer some major problems, for example its constringency rate is not too fast for a large amount of datasets. To overcome these defects, an efficient fuzzy Kohonen network algorithm is proposed in this...
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