K-nearest neighbors algorithm - definição. O que é K-nearest neighbors algorithm. Significado, conceito
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O que (quem) é K-nearest neighbors algorithm - definição


K-nearest neighbors algorithm         
  • Calculation of the border ratio.
  • Example of ''k''-NN classification. The test sample (green dot) should be classified either to blue squares or to red triangles.

If ''k = 3'' (solid line circle) it is assigned to the red triangles because there are 2 triangles and only 1 square inside the inner circle.

If ''k = 5'' (dashed line circle) it is assigned to the blue squares (3 squares vs. 2 triangles inside the outer circle).
  • Three types of points: prototypes, class-outliers, and absorbed points.
CLASSIFICATION ALGORITHM
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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         
  • Tomb of Maj. Robert S. 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.