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Issue No. 04 - April (2010 vol. 32)
ISSN: 0162-8828
pp: 766-768
Hui Wang , University of Ulster, Jordanstown, Newtownabbey, Co. Antrim
The neighborhood counting measure (NCM) is a similarity measure based on the counting of all common neighborhoods in a data space [5]. The minimum risk metric (MRM) [2] is a distance measure based on the minimization of the risk of misclassification. The paper by Argentini and Blanzieri [1] refutes a remark in [5] about the time complexity of MRM, and presents an experimental comparison of MRM and NCM. This paper is a response to the paper by Argentini and Blanzieri [1]. The original remark is clarified by a combination of theoretical analysis of different implementations of MRM and experimental comparison of MRM and NCM using straightforward implementations of the two measures.
Minimum risk metric, neighborhood counting measure, k-nearest neighbor.
Hui Wang, "Neighborhood Counting Measure and Minimum Risk Metric", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 32, no. , pp. 766-768, April 2010, doi:10.1109/TPAMI.2010.16
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