Exploiting regions of influence to visualize class boundaries

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dc.contributor.author Tinna, Pallav
dc.contributor.author Karlapalem, Kamalakar
dc.contributor.other IS&T International Symposium on Electronic Imaging (EI 2016)
dc.coverage.spatial San Francisco, US
dc.date.accessioned 2016-04-16T11:49:26Z
dc.date.available 2016-04-16T11:49:26Z
dc.date.issued 2016-02-14
dc.identifier.citation Tinna, Pallav and Karlapalem, Kamalakar, “Exploiting regions of influence to visualize class boundaries”, in the IS&T International Symposium on Electronic Imaging (EI 2016), Hilton San Francisco Union Square, San Francisco, US, Feb. 14-18, 2016. en_US
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/2184
dc.description.abstract Interactive visualization and analysis of the class boundaries is important because it tells us how and why the classes differ. However, the problem of modeling the boundary of classes of arbitrary size, shape and density is challenging. The boundary of a class should not be limited to the points/shape which encloses the points within the class but it should be, the points/shape which encloses the region of influence of a class. The "region of influence" refers to the space around the class where any point lying within the region is likely to be classified to the class based on a nearest neighbor classifier. We have developed interactive boundary visualization toolkit for classified datasets which provides insights about the classifier model used on the dataset. Our algorithm first generates a candidate boundary set for each class based on reverse k-nearest neighbors approach and extends this boundary iteratively through the region of influence of the class. Further, we present these boundary points enclosing the region of influence as a linear approximated shape using triangulation techniques. We show experimental results on 2D and 3D datasets. en_US
dc.description.statementofresponsibility by Pallav Tinna and Kamalakar Karlapalem
dc.language.iso en_US en_US
dc.publisher Society for Imaging Science and Technology en_US
dc.subject Dataset en_US
dc.subject Class boundaries en_US
dc.subject 2D en_US
dc.subject 3D en_US
dc.subject Algorithm en_US
dc.title Exploiting regions of influence to visualize class boundaries en_US
dc.type Article en_US


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