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Title: Technique for fast and efficient hierarchical clustering

Abstract

A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

Inventors:
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1108968
Patent Number(s):
8554771
Application Number:
12/636,898
Assignee:
Sandia Corporation (Albuquerque, NM)
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION

Citation Formats

Stork, Christopher. Technique for fast and efficient hierarchical clustering. United States: N. p., 2013. Web.
Stork, Christopher. Technique for fast and efficient hierarchical clustering. United States.
Stork, Christopher. Tue . "Technique for fast and efficient hierarchical clustering". United States. https://www.osti.gov/servlets/purl/1108968.
@article{osti_1108968,
title = {Technique for fast and efficient hierarchical clustering},
author = {Stork, Christopher},
abstractNote = {A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Oct 08 00:00:00 EDT 2013},
month = {Tue Oct 08 00:00:00 EDT 2013}
}

Works referenced in this record:

Efficient algorithms for agglomerative hierarchical clustering methods
journal, December 1984


Fast hierarchical clustering and other applications of dynamic closest pairs
journal, December 2000


A fast encoding algorithm for vector quantization
journal, December 1997