TITLE

The Development of Invisible Data Mining Functionality for Discovering Interesting Knowledge: In the case of Bioinformatics

AUTHOR(S)
Gebremeskel, Gebeyehu Belay; Zhongshi He; Yuanyuan Jia
PUB. DATE
March 2013
SOURCE
Journal of Convergence Information Technology;Mar2013, Vol. 8 Issue 5, p1246
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The discovery of interesting knowledge is the ultimately desired result from the DM sequence of processes. Therefore, in this paper, we discussed the algorithms and the invisible DM functionality operators on extracting interesting knowledge from medical data sets towards patient safety care. The data set containing a set of variables, which describe the characteristics and behaviors of medical data sets to explore and visualize the hidden valuable information from the database. For the challenges of KD in biomedical data sets, we introduced new and combining intelligent approaches: the algorithms of the development of invisible DM functionality, and visualization of the mining process. The issues have been discussed based on real data sets of medical data.
ACCESSION #
100165149

 

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