Nearest Neighbor Pattern Classification.

Cover, T. M., & Hart, P. E. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13(1), 21-27.

Type

Journal article

Intellectual base

Primary research

Year

1967

DOI

10.1109/tit.1967.1053964

Link

https://doi.org/10.1109/TIT.1967.1053964

Cited from

philosophy, psychology

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Classification
  • Decision trees, logistic regression, support-vector machines, and neural networks learn classifiers from labeled training data, building on foundational pattern-classification results such as Cover and Hart (1967) on nearest-neighbor decision rules.

    This sourceFoundational result in machine-learning classification: establishes the asymptotic error bound of the nearest-neighbor decision rule, anchoring large-scale automated category assignment.

• Exemplar Retrieval
  • In machine learning k-nearest-neighbours, kernel methods, and retrieval-augmented generation are exemplar systems, while logistic regression, decision trees, and parametric classifiers are prototype systems; vector-database retrieval feeding a model is the most visible recent return to exemplar architecture at scale.

    This sourceFoundational analysis of the k-nearest-neighbour classifier, the canonical non-parametric, instance-based (exemplar) method whose model is the stored training set itself; the same case base under a different distance metric yields different answers.

Verification

This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.

Registry ID ref:105a4c006d59 · see in the full table