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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
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Jones, Christian Birk. Laterally Primed Adaptive Resonance Theory. Computer software. Vers. 00. USDOE. 19 Jul. 2017. Web.
Jones, Christian Birk. (2017, July 19). Laterally Primed Adaptive Resonance Theory (Version 00) [Computer software].
Jones, Christian Birk. Laterally Primed Adaptive Resonance Theory. Computer software. Version 00. July 19, 2017.
@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.},
doi = {},
year = 2017,
month = 7,
note =
}

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