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Pattern classification or clustering plays important role in a wide variety of applications in different areas like psychology and other social sciences, biology and medical sciences, pattern recognition and data mining. A lot of algorithms for supervised or unsupervised classification have been developed so far in order to achieve high classification accuracy with lower computational cost. However,...
A novel feature selection approach is proposed for data space defined over continuous features, which obtains a subset of features,such that it can discriminate class labels of objects and its discriminant ability is not inferior to that of the original features,so to effectively improve the learning performance and intelligibility of the classification model. According to the spatial distribution...
Most of the fuzzy classifiers are created by fuzzy rules based on apriori knowledge and expert's knowledge, but in many applications, it's difficult to obtain fuzzy rules without apriori knowledge of the data. To solve this problem, a new way of creating Mamdani fuzzy classifier based on Mamdani fuzzy logical system is proposesed in this paper, and the new fuzzy classifier is improved with the genetic...
Information is getting more and more today, how to handle high dimensions data and high complexity data are the key issues of this contribution. Multi-attribute data usually possesses high data dimension and high data complexity. In order to solve these problems, the contribution proposes a new information fusion model which is briefly described as follows: (1) Reduce data dimensions by principal...
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