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, Author (s) Details
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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