ABSTRACT. The K-Nearest Neighbor search (kNN) problem has been investi- gated extensively in the past due to its broad range of applications.
K-Nearest Neighbor Search for Fuzzy Objects - ResearchGate
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Reverse nearest neighbor queries are useful in identifying objects that are of significant influence or importance. Existing methods either rely on pre- ...
Jun 6, 2010 · In this paper, we propose two new kinds of kNN queries for fuzzy objects, Ad-hoc kNN query (AKNN) and Range kNN query (RKNN), to find the k ...
Aug 29, 2024 · The theory of fuzzy sets is introduced into the k-nearest Neighbor technique to develop a fuzzy version of the algorithm. Three Methods of ...
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In this paper, we propose two new kinds of kNN queries for fuzzy objects, Ad-hoc kNN query (AKNN) and Range kNN query (RKNN), to find the k nearest objects ...
Jan 19, 2018 · The KNN algorithm assumes that similar things exist in close proximity. In other words, similar things are near to each other. Notice in the ...
The theory of fuzzy sets is introduced into the AT-nearest neighbor technique to develop a fuzzy version of the algorithm.
Aug 21, 2022 · In this paper, we propose a new kNN algorithm, ie, Fuzzy Parameterized Fuzzy Soft kNN (FPFS-kNN), based on multiple pseudo-metrics of fuzzy parameterized fuzzy ...
Classification of objects is an important area of research and of practical ... The fuzzy K-nearest neighbor algorithm assigns class membership to a ...
We present a new generalized version of the fuzzy k-nearest neighbor (FKNN) classifier that uses local mean vectors and utilizes the Bonferroni mean.