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 information of ordinal attribute, a new dissimilarity measure for the k-Modes algorithm...
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...
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...
[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 ...
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- ...
cretizationonthesenominalattributesdirectly,thedisorderofthenominalattributesisdestructed.Thusthedictioneffect oftraditionalintrusiondetectionmethodsisnotsatisfied.Inthispaper,weproposeanetworkintrusiondetectionalgo原 rithmbasedonnominalvariablesvectorization.Theproposedalgorithmfirstlydovectorizationforthenominalattributes. Then...
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 ...
A fast way for determining the best subset test for a nominal attribute in a decision tree. When a nominal attribute has n distinct values, the prior art requires computing the impurity functions on each of the 2.sup.n-1 -1 possible subset partitioning of the n values and finding the ...