Current Search: Eroglu, Cemal. (x)
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Title
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An empirical study of combining techniques in software quality classification.
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Creator
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Eroglu, Cemal., Florida Atlantic University, Khoshgoftaar, Taghi M.
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Abstract/Description
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In the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using...
Show moreIn the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using clustering techniques some base-level classifiers were eliminated from the hybrid learner input. We had three different experiments each with a different number of base-level classifiers. We empirically show that the hybrid learning approach generally yields better performance than the best selected base-level learners and majority voting under some conditions.
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Date Issued
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2004
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PURL
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http://purl.flvc.org/fcla/dt/13162
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Subject Headings
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Computer software--Testing, Computer software--Quality control, Computational learning theory, Machine learning, Digital computer simulation
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Format
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Document (PDF)
