DESCRIPTION

Package: pmml
Type: Package
Title: Generate PMML for Various Models
Version: 2.5.2
Authors@R: c(
    person("Dmitriy", "Bolotov", email = "dmitriy.bolotov@softwareag.com", role = c("aut", "cre")),
    person("Tridivesh", "Jena", email = "tridivesh.jena@softwareag.com", role = "aut"),
    person("Graham", "Williams", email = "graham.williams@togaware.net", role = "aut"),
    person("Wen-Ching", "Lin", role = "aut"),
    person("Michael", "Hahsler", email = "michael@hahsler.net", role = "aut"),
    person("Hemant", "Ishwaran", role = "aut"),
    person("Udaya B.", "Kogalur", role = "aut"),
    person("Rajarshi", "Guha", email = "rguha@indiana.edu", role = "aut"),
    person("Software AG", role = c("cph")))
Depends:
    XML
Suggests:
    ada,
    amap,
    arules,
    caret,
    clue,
    data.table,
    forecast,
    gbm,
    glmnet,
    Matrix,
    neighbr,
    nnet,
    rpart,
    randomForest,
    rattle,
    kernlab,
    e1071,
    testthat,
    survival,
    xgboost,
    knitr,
    rmarkdown,
    covr,
    tibble
Imports:
    methods,
    stats,
    utils,
    stringr
License: GPL-3 | file LICENSE
Description: The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://dmg.org/>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products. The package isofor (used for anomaly detection) can be installed with devtools::install_github("gravesee/isofor").
URL: https://open-source.softwareag.com/r-pmml/, https://github.com/SoftwareAG/r-pmml, https://www.softwareag.com/corporate/products/az/zementis/default.html
BugReports: https://github.com/SoftwareAG/r-pmml/issues
NeedsCompilation: no
RoxygenNote: 7.1.2
VignetteBuilder: knitr
Encoding: UTF-8