In this paper, the limitations of some existing dissimilarity measure of k-Modes algorithm in mixed ordinal and nominal data are analyzed by using some illustrative examples. Based on the idea of mining ordinal
and an object entropy based on attribute granules is proposed. Finally, a nominal data-oriented outlier detection method is explored based on the proposed object entropy. The experimental results show that the proposed detection method can effectively detect outliers in nominal data. Besides, the resu...
The method proposed in this paper is suitable for lattice data with one nominal attribute. Accordingly, we restrict our discussion to the lattices with only one nominal attribute. For convenience, we review some notations in this section. Definition 2.1 A one nominal attribute lattice is a pair...
Rough set theory is an essential tool for measuring uncertainty, which has been widely applied in attribute reduction algorithms. Most of the related researches focus on how to update the lower and the upper approximation operator to match data characteristics or how to improve the efficiency of th...
[6] proposed a data stream clustering technique which clusters similar data streams based on the correlation of the attribute values. It uses a sliding window technique, and for each window, a fractal value is calculated in a fractal dimension, which is a reduced dimension of the original ...
cretizationonthesenominalattributesdirectly,thedisorderofthenominalattributesisdestructed.Thusthedictioneffect oftraditionalintrusiondetectionmethodsisnotsatisfied.Inthispaper,weproposeanetworkintrusiondetectionalgo原 rithmbasedonnominalvariablesvectorization.Theproposedalgorithmfirstlydovectorizationforthenominalattributes. Then...
used to transform nominal attributes into binary integer ones. In section three we will discuss how to compute the distance between two data points by the use of the Olary transformation. Section four contains the running process of the Olary algori- ...
III. THE DISTANCE METRIC Before calculating the distance between two data points, a transforming process must be done. In other words, all the original nominal attributes must be transformed into integer ones by the use of the Olary code. And each integer attribute Proceedings of the ...
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Then, information entropy is introduced into the formal context, and an object entropy based on attribute granules is proposed. Finally, a nominal data-oriented outlier detection method is explored based on the proposed object entropy. The experimental results show that the proposed detection method ...