An Empirical Study on the Effect of the Class Imbalance on the Performance of Classifiers and Estimating Performance
Journal Title: International Journal of Engineering and Science Invention - Year 2017, Vol 6, Issue 9
Abstract
One of the ebb and flow imperative difficulties in information mining examination is arrangement under an imbalanced information dissemination. This issue shows up when a classifier needs to recognize an uncommon, however vital case. Customarily, spaces in which class awkwardness is predominant incorporate misrepresentation or interruption identification, restorative analysis, chance administration, content arrangement and data recovery. Later reports incorporate unexploded weapons identification or mine discovery. A characterization issue is imbalanced if, in the accessible information, a specific class is spoken to by few examples contrasted with alternate classes. By and by, the issue is tended to with 2-class issues; multiclass issues are meant paired. As the minority occasions are of more prominent intrigue, they are alluded to as positive examples (positive class); the dominant part class is alluded to as the negative class.
Authors and Affiliations
Prof. Dr. G. Manoj Someswar, Mukiri Ratna Raju
Keywords
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- EP ID EP403318
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