Encog: Library of Interchangeable Machine Learning Models for Java and C\#

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Jeff Heaton",
  title =        "{Encog}: Library of Interchangeable Machine Learning
                 Models for {Java} and {C\#}",
  journal =      "Journal of Machine Learning Research",
  year =         "2015",
  volume =       "16",
  pages =        "1243--1247",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1533-7928",
  URL =          "http://www.jmlr.org/papers/v16/",
  URL =          "http://jmlr.org/papers/v16/heaton15a.html",
  URL =          "http://www.jmlr.org/papers/volume16/heaton15a/heaton15a.pdf",
  abstract =     "This paper introduces the Encog library for Java and
                 C#, a scalable, adaptable, multi-platform machine
                 learning framework that was first released in 2008.
                 Encog allows a variety of machine learning models to be
                 applied to data sets using regression, classification,
                 and clustering. Various supported machine learning
                 models can be used interchangeably with minimal
                 recoding. Encog uses efficient multithreaded code to
                 reduce training time by exploiting modern multicore
                 processors. The current version of Encog can be
                 downloaded from www.encog.org.",

Genetic Programming entries for Jeff Heaton