Metric Considerations in Cluster Analysis.

Abstract

A variation of the 'k-means' method of cluster analysis is described which is designed to take into account and profit from the possibility that the separate clusters resemble samples from multivariate normal distributions with substantially different covariance structures. These covariance structures determine metrics which can be updated recursively. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 20, 1970
Accession Number
AD0714810

Entities

People

  • Herman Chernoff

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Covariance
  • Data Science
  • Distribution Functions
  • Functions (Mathematics)
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics
  • Normal Distribution

Readers

  • Linear Algebra
  • Neural Network Machine Learning.
  • Systems Analysis and Design