{
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  "Package": "RSNNS",
  "Maintainer": "Christoph Bergmeir <c.bergmeir@decsai.ugr.es>",
  "License": "LGPL (>= 2) | file LICENSE",
  "Title": "Neural Networks using the Stuttgart Neural Network Simulator\n(SNNS)",
  "Type": "Package",
  "LazyLoad": "yes",
  "Authors@R": "c(\nperson(\"Christoph\", \"Bergmeir\", email = \"c.bergmeir@decsai.ugr.es\", role = c(\"aut\", \"cre\", \"cph\")),\nperson(\"José M.\", \"Benítez\", role = c(\"ths\")),\nperson(\"Andreas\", \"Zell\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Niels\", \"Mache\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Günter\", \"Mamier\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Michael\", \"Vogt\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Sven\", \"Döring\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Ralf\", \"Hübner\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Kai-Uwe\", \"Herrmann\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Tobias\", \"Soyez\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Michael\", \"Schmalzl\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Tilman\", \"Sommer\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Artemis\", \"Hatzigeorgiou\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Dietmar\", \"Posselt\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Tobias\", \"Schreiner\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Bernward\", \"Kett\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Martin\", \"Reczko\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Martin\", \"Riedmiller\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Mark\", \"Seemann\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Marcus\", \"Ritt\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Jamie\", \"DeCoster\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Jochen\", \"Biedermann\", role = c(\"ctb\"), comment= \"Part of original SNNS external contributors\"),\nperson(\"Joachim\", \"Danz\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Christian\", \"Wehrfritz\", role = c(\"ctb\"), comment= \"Part of original SNNS development team\"),\nperson(\"Patrick\", \"Kursawe\", role = c(\"ctb\"), comment= \"Contributors to SNNS Version 4.3\"),\nperson(\"Andre\", \"El-Ama\", role = c(\"ctb\"), comment= \"Contributors to SNNS Version 4.3\"))",
  "Copyright": "Original SNNS software Copyright (C) 1990-1995 SNNS Group,\nIPVR, Univ. Stuttgart, FRG; 1996-1998 SNNS Group, WSI, Univ.\nTuebingen, FRG. R interface Copyright (C) DiCITS Lab, Sci2s\ngroup, DECSAI, University of Granada.",
  "Description": "The Stuttgart Neural Network Simulator (SNNS) is a library\ncontaining many standard implementations of neural networks.\nThis package wraps the SNNS functionality to make it available\nfrom within R. Using the 'RSNNS' low-level interface, all of\nthe algorithmic functionality and flexibility of SNNS can be\naccessed. Furthermore, the package contains a convenient\nhigh-level interface, so that the most common neural network\ntopologies and learning algorithms integrate seamlessly into R.",
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  "BugReports": "https://github.com/cbergmeir/RSNNS/issues",
  "MailingList": "rsnns@googlegroups.com",
  "Date": "2026-01-30",
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    "extra/citation.json",
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    "plotIterativeError",
    "plotRegressionError",
    "plotROC",
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    "rbfDDA",
    "readPatFile",
    "readResFile",
    "resolveSnnsRDefine",
    "rsnnsObjectFactory",
    "savePatFile",
    "setSnnsRSeedValue",
    "SnnsRObjectFactory",
    "som",
    "splitForTrainingAndTest",
    "toNumericClassLabels",
    "train",
    "vectorToActMap",
    "weightMatrix"
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      "title": "",
      "object": "snnsData",
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