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Title: Laterally Primed Adaptive Resonance Theory

Abstract

LAPART is an artificial neural network algorithm written in the Python programming language. The algorithm can learn patterns using multi-dimensional hyper boxes. It can also perfrom regression and classification calculations based on learned associations.

Authors:
 [1]
  1. Sandia National Laboratories
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1373351
Report Number(s):
LAPART; 005383MLTPL00
SCR# 2217
DOE Contract Number:
AC04-94AL85000
Resource Type:
Software
Software Revision:
00
Software Package Number:
005383
Software CPU:
MLTPL
Open Source:
Yes
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Jones, Christian Birk. Laterally Primed Adaptive Resonance Theory. Computer software. https://www.osti.gov//servlets/purl/1373351. Vers. 00. USDOE. 19 Jul. 2017. Web.
Jones, Christian Birk. (2017, July 19). Laterally Primed Adaptive Resonance Theory (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1373351.
Jones, Christian Birk. Laterally Primed Adaptive Resonance Theory. Computer software. Version 00. July 19, 2017. https://www.osti.gov//servlets/purl/1373351.
@misc{osti_1373351,
title = {Laterally Primed Adaptive Resonance Theory, Version 00},
author = {Jones, Christian Birk},
abstractNote = {LAPART is an artificial neural network algorithm written in the Python programming language. The algorithm can learn patterns using multi-dimensional hyper boxes. It can also perfrom regression and classification calculations based on learned associations.},
url = {https://www.osti.gov//servlets/purl/1373351},
doi = {},
year = {Wed Jul 19 00:00:00 EDT 2017},
month = {Wed Jul 19 00:00:00 EDT 2017},
note =
}

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