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K-Nearest Neighbors/Evidence
Method evidence record

K-Nearest Neighbors

K-Nearest Neighbors (KNN), formalized by Cover and Hart in 1967, is a non-parametric, instance-based method that classifies or predicts a new observation by looking at the k closest examples in the training data. For classification it takes a majority vote among those neighbors; for regression it averages their values.

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K-Nearest Neighbors (KNN) Classification and Regression
Taxonomic method record · ml-model / machine-learning
  • Cover, T.M. & Hart, P.E. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13(1), 21–27. · DOI 10.1109/TIT.1967.1053964
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyDecision Treemachine-suggested · Relational suggestion, not evidence.See alsoLogistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyNaive Bayesmachine-suggested · Relational suggestion, not evidence.Same method familyRandom Forestmachine-suggested · Relational suggestion, not evidence.Same method familySupport Vector Machinemachine-suggested · Relational suggestion, not evidence.

Evidence status

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Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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