A. Pethalakshmi

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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)
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)
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)
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)
Clustering is widely used technique in data mining application for discovering patterns in large data set. In this paper the K-Means and Fuzzy C-Means algorithm is analyzed and found that quality of the resultant cluster is based on the initial seeds where it is selected either sequentially or randomly. For real time large database it's difficult to predict(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)
The term ETL which stands for Extraction, Transformation, and Loading is a batch or scheduled data integration process that includes extracting data from their operational or external data sources, transforming the data into an appropriate format, and loading the data into a data warehouse repository. Through the study of Extract, Transform, and Load (ETL)(More)