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Aiming to these presented frequent neighboring class set mining algorithms have some repeated computing and redundancy candidate frequent neighboring class set when these algorithms extract frequent neighboring class set, this paper proposes an algorithm of mining frequent neighboring class set based on increasing sequence, which is suitable for mining frequent neighboring class set of objects in...
Case based reasoning (CBR) is very important task in data mining, but privacy information will be disclosed easily in CBR. This paper presents random locally linear embedding (LLE) on encrypted case based reasoning method. In order to be ensure the security of the CBR, the parameters nearest neighbor number k and embedded space dimension d of LLE algorithm are selected randomly. Further we embed the...
In this paper, we present a closed labeled tree mining algorithm, FBMiner, based on the add-remove principle of closed sets which is newly introduced. Also, we propose a time-decay module to solve stream data mining which gives more attention on the latest data. Compared to the traditional mining algorithms in data stream, FBMiner performs well even that the data is of high complexity. The experiment...
The granularity is used to describe decision knowledge based on the concept of rough degree in rough theory. The rule distance are put forward, and a feasible distance formula between different rules is constructed according to the requirement of describing the distance between different rules and the definition of attribute signification in information system. Both of the n-dimensional knowledge...
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