Visualizing and Interacting with Kernelized Data

IEEE Transactions on Visualization and Computer Graphics
A BarbosaL Gustavo Nonato

Abstract

Kernel-based methods have experienced a substantial progress in the last years, tuning out an essential mechanism for data classification, clustering and pattern recognition. The effectiveness of kernel-based techniques, though, depends largely on the capability of the underlying kernel to properly embed data in the feature space associated to the kernel. However, visualizing how a kernel embeds the data in a feature space is not so straightforward, as the embedding map and the feature space are implicitly defined by the kernel. In this work, we present a novel technique to visualize the action of a kernel, that is, how the kernel embeds data into a high-dimensional feature space. The proposed methodology relies on a solid mathematical formulation to map kernelized data onto a visual space. Our approach is faster and more accurate than most existing methods while still allowing interactive manipulation of the projection layout, a game-changing trait that other kernel-based projection techniques do not have.

References

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Oct 29, 2011·IEEE Transactions on Visualization and Computer Graphics·Paulo JoiaLuis Gustavo Nonato
Sep 21, 2013·IEEE Transactions on Visualization and Computer Graphics·Xinran HuScotland Leman
Jan 1, 2012·IEEE Computer Graphics and Applications·J AlsakranShixia Liu

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