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}
}
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Fast hierarchical clustering and other applications of dynamic closest pairs
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- Eppstein, David
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