A. Pethalakshmi

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Unsupervised clustering is an essential technique in Datamining. Since feature selection is a valuable technique in data analysis for information preserving data reduction, researchers have made use of the rough set theory to construct reducts by which the unsupervised clustering is changed into the supervised reduct. Rule identification involves the(More)
A rough set theory is a newmathematical tool to deal with uncertainty and vagueness of decision system and it has been applied successfully in all the fields. It is used to identify the reduct set of the set of all attributes of the decision system. The reduct set is used as preprocessing technique for classification of the decision system in order to bring(More)
Web usage mining exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web (WWW) users. The required information is captured by Web servers and stored in Web usage data logs. The first phase of Web usage mining is the pre processing phase. In the preprocessing phase, first, relevant information is filtered(More)
Fuzzy approaches can play an important role in data mining, because they provide comprehensible results. In addition, the approaches studied in data mining have mainly been oriented at highly structured and precise data. In this paper, we examine the performance of four fuzzy classifiers on heart data. The fusion of Fuzzy Logic with the classifiers Decision(More)
The volume of data being generated nowadays is increasing at phenomenal rate. Extracting useful knowledge from such data collections is an important and challenging issue. A promising technique is the rough set theory, a new mathematical approach to data analysis based on classification of objects of interest into similarity classes, which are indiscernible(More)
Efficient utilization of resources is the key factor for any environment. The grid environment is also more dynamic, it facilitates the movement of resources in and out of the environment flexibly. Hence maintenance of centralized registries is not sufficient for this demanding environment. Here, we propose a new approach for resource discovery which(More)
Microcalcification on X-ray mammogram is a significant mark for early detection of breast cancer. Texture analysis methods can be applied to detect clustered microcalcification in digitized mammograms. In order to improve the predictive accuracy of the classifier, the original number of feature set is reduced into smaller set using feature reduction(More)
Molecular computing is a discipline that aims at harnessing individual molecules for computational purposes. This paper presents the applied Mathematical sciences using DNA molecules. The Major achievements are outlined the potential advances and the challenges for the practitioners in the foreseeable future. The Binary Optimization in Linear Programming is(More)
Customer relationship management (CRM) has become a strategic initiative aimed at getting, growing, and retaining the right customers. A great amount of numeric data and even more soft information are available about customers. In this paper we analyze the relative importance of factors and the priority of the schemes by constructing the CRM hierarchy model(More)