Exploiting the relationships among several binary classifiers via data transformation |
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Authors: | Kar-Ann Toh Geok-Choo Tan |
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Affiliation: | 1. School of Electrical & Electronic Engineering, Yonsei University, Seoul 120-749, Korea;2. Division of Mathematical Sciences, School of Physical & Mathematical Sciences, Nanyang Technological University, Singapore 639798, Singapore |
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Abstract: | The structural resemblance among several existing classifiers has motivated us to investigate their underlying relationships. By exploring into the mapping solutions of these classifiers, we found that they can be linked by simple feature data scaling. In other words, the key to these relationships lies upon how the replica of feature data are being scaled. This finding leads us directly to an exploration of novel classifiers beyond existing settings. Based on an extensive empirical evaluation, we show that the proposed formulation facilitates a tuning capability beyond existing settings for classifier generalization. |
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Keywords: | Binary classification Linear estimation methods Deterministic methods Area under the ROC curve |
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