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Fast Most Similar Neighbor (MSN) classifiers for Mixed Data
(Revista Computación y Sistemas; Vol. 14 No.1, 2010-09-30)
Abstract. The k nearest neighbor (k-NN) classifier has been extensively used in Pattern Recognition because of its simplicity and its good performance. However, in large datasets applications, the exhaustive k-NN classifier ...
Fast k most similar neighbor classifier for mixed data (tree k-MSN)
(Elsevier Ltd, 2010)
Fast k most similar neighbor classifier for mixed data (tree k-MSN)
(Elsevier Ltd, 2010)
Classifica????o de obst??culos baseada no classificador k-nearest neighbors aplicada a um rob?? de inspe????o de linha de transmiss??o
(Escola Polit??cnica, Departamento de Engenharia El??tricaem Engenharia El??tricaUFBAbrasil, 2019-05-14)
A comparison between k-Optimum Path Forest and k-Nearest Neighbors supervised classifiers
(Elsevier Science BvAmsterdamHolanda, 2014)
Adding diversity to rank examples in anytime nearest neighbor classification
(IEEE Systems, Man, and Cybernetics Society - IEEE SMCWayne State UniversityDetroit, 2014-12)
In the last decade we have witnessed a huge increase of interest in data stream learning algorithms. A stream is na ordered sequence of data records. It is characterized by properties such as the potentially infinite and ...
An efficient algorithm for approximated self-similarity joins in metric spaces
(Elsevier, 2020)
Similarity join is a key operation in metric databases. It retrieves all pairs of elements that are similar. Solving such a problem usually requires comparing every pair of objects of the datasets, even when indexing and ...