In the product business, it is fundamental that reduction time and endeavors in programming improvement. Programming reusability is a significant measure to improve the advancement and nature of programming. Improving reusability will diminish conveyance time of programming items, diminishes the improvement exertion and furthermore programming mistakes and cost of advancement procedure. Programming reuse is the best arrangement factor to secure the current information from the programming distribution warehouse. Estimating the reusability level of the product is fundamental to accomplish the objectives of reuse. Information mining is the way toward extracting helpful patterns and breakdown data sets from huge information collections. The reusability of a product segment picks the correct estimation and upgrades the certainty of a function for reuse. The software metrics are utilized as quantitative measures to set up and assess the parts. In this paper estimating the product reusability utilizing several classification algorithms on a particular programming reuse data set are connected. The framework is actualized utilizing the R information mining tool and execution of the computerized framework is created for reusability expectation like accuracy, review, f-measure. The test result demonstrates the representation can be viably utilized wasteful, precise, and speedier and is financial for distinguishing proof of reusable parts from the current programming assets. This document seeks to gives comparative analysis of H-SOM and Naïve Bayes algorithm classifiers of Dengue datasets.

Author (s)  Details

Mrs. G. Maheswari,
Department of Computer Science, Madurai Kamraj University, Madurai, Tamilnadu, India.

Dr. K. Chitra,
Department of Computer Science, Government Arts College, Melur, Madurai, Tamilnadu, India.

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