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- W2171203510 abstract "Aim at the faults of Dynamic Clustering Algorithm based on Fuzzy Equation Matrix, we raise a fuzzy clustering algorithm based on factor analysis, which it combines the technology of reducing dimension using factor analyses method. The algorithm will deal with the sample collections before fuzzy clustering, which enlarge the scale of using dynamic clustering algorithm to resolve practical problems. All these show that the algorithm has a strong capability of concluding and abstracting through being applied to E-mail filtering. At the same time, we also make an experiment in our optional database. The experiment result verifies that the algorithm recall rate is 87.3 % in the mail filtering, which is higher than the SVM’s 80.1%, Naive Bayes’s 61.7%, and KNN’s 73.2% respectively. The experiments show that the new algorithm has better recall rate and error rate." @default.
- W2171203510 created "2016-06-24" @default.
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- W2171203510 date "2009-02-01" @default.
- W2171203510 modified "2023-09-26" @default.
- W2171203510 title "Fuzzy Clustering Algorithm based on Factor Analysis and its Application to Mail Filtering" @default.
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- W2171203510 doi "https://doi.org/10.4304/jsw.4.1.58-64" @default.
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