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Qu'est-ce (qui) est K-nearest neighbors algorithm - définition
K-nearest neighbors algorithm
CLASSIFICATION ALGORITHM
Nearest neighbor (pattern recognition); Nearest Neighbor (Pattern Recognition); K-Nearest Neighbor algorithm; K-nearest-neighbor estimator; K-nearest neighbour algorithm; K-nearest neighbor; K-nearest neighbour; K-NN; Ibk algorithm; K nearest neighbors; K-nearest neighbours algorithm; K-nearest neighbors; K-nearest neighbors problem; K-nearest neighbor problem; K-Nearest Neighbours; K-nearest-neighbor; K-nearest-neighbor algorithm; Nearest neighbour classifiers; K-nearest neighbor algorithm; K-nearest neighbors classification; K-Nearest Neighbors; K-Nearest Neighbour; Nearest neighbors classifier; K-NN regression; K-NN algorithm; KNN lookup; KNN algorithm; Nearest neighbor decision rule
In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover. It is used for classification and regression.
False nearest neighbor algorithm
Within abstract algebra, the false nearest neighbor algorithm is an algorithm for estimating the embedding dimension. The concept was proposed by Kennel et al.
Robert Neighbors
TEXAS INDIAN AGENT, TEXAS POLITICIAN
Robert Simpson Neighbors; Robert S. Neighbors; Camp Cooper; Neighbors, Robert
Robert Simpson Neighbors (November 3, 1815 – September 14, 1859) was an Indian agent and Texas state legislator. Known as a fair and determined protector of Indian interests as guaranteed by treaty, he was murdered for his beliefs by a Texan who disagreed with giving any rights to the Comanches.
