Abstract
The nearest neighbor classification method assigns to an unclassified point the class of the nearest of a set of previously classified points. An extension to this approach is the K-NN method, in which the classification is made taking into account the K nearest points and classifying the unclassified point by a voting criteria from this k points. We present a new method that extends the K-NN limits, taking into account, for each neighbor, its I nearest neighbors. Experimental results are promising, obtaining better results for two class problems than the original K-NN.
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Mendialdua, I., Sierra, B., Lazkano, E., Irigoien, I., Jauregi, E. (2010). Surrounding Influenced K-Nearest Neighbors: A New Distance Based Classifier. In: Cao, L., Feng, Y., Zhong, J. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17316-5_26
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DOI: https://doi.org/10.1007/978-3-642-17316-5_26
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