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EnglishIn a 2006 TPAMI paper, Wang proposed the Neighborhood Counting Measure [2], a similarity measure for the k-NN algorithm. In his paper, Wang mentioned the Minimum Risk Metric (MRM, [1]), an early distance measure based on the minimization of the risk of misclassification. Wang did not compare NCM to MRM because of its allegedly excessive computational load. In this comment paper, we complete the comparison that was missing in Wang’s paper and, from our empirical evaluation, we show that MRM outperforms NCM and that its running time is not prohibitive as Wang suggested.
| Titolo: | About Neighborhood Counting Measure Metric and Minimum Risk Metric |
| Autori Unitn: | |
| Anno di pubblicazione: | 2010 |
| Titolo del periodico: | |
| Abstract: | In a 2006 TPAMI paper, Wang proposed the Neighborhood Counting Measure [2], a similarity measure for the k-NN algorithm. In his paper, Wang mentioned the Minimum Risk Metric (MRM, [1]), an early distance measure based on the minimization of the risk of misclassification. Wang did not compare NCM to MRM because of its allegedly excessive computational load. In this comment paper, we complete the comparison that was missing in Wang’s paper and, from our empirical evaluation, we show that MRM outperforms NCM and that its running time is not prohibitive as Wang suggested. |
| Handle: | http://hdl.handle.net/11572/89842 |
| Appare nelle tipologie: | 03.1 Articolo su rivista (Journal article) |
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