Some Methods for Classification and Analysis of Multivariate Observations.

MacQueen, J. (1967). Some Methods for Classification and Analysis of Multivariate Observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1, 281-297.

Type

Conference paper

Intellectual base

Primary research

Year

1967

Link

https://projecteuclid.org/euclid.bsmsp/1200512992

Cited from

data_science, mathematics

Cited by

3 citations across 3 artifacts.

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

Primes

• Local Optimum
  • In machine learning it is k-means halting at an initialisation-dependent local optimum and the standard escape family — random restarts, simulated annealing, momentum — built precisely to address it.

    This sourceIntroduces k-means; the within-cluster sum-of-squares objective and its initialization-dependent local optima.

• Segmentation and Boundary Drawing
  • Segmentation and boundary drawing encodes a signature pattern: continuous domain → threshold decisions → discrete partitions → encoded meaning, a structure that MacQueen (1967) operationalized in his foundational k-means treatment of partitioning N-dimensional populations into k discrete sets via threshold placement.

    This sourceFoundational k-means treatment: partitions an N-dimensional continuous population into k discrete sets via threshold placement minimizing within-class variance.

Domain-specific

• K-means clustering
  • Conceptual clustering identity only; high-stakes grouping requires bias, stability, privacy, construct-validity, and domain-impact review.

Verification

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