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pmml

Overview

Export various machine learning and statistical models to PMML and generate data transformations in PMML format.

For a description of the supported packages, see the vignette: Supported Packages and Additional Functions.

Installation

You can install the released version of pmml from CRAN with:

install.packages("pmml")

Example

library(pmml)

# Build an lm model
iris_lm <- lm(Sepal.Length ~ ., data=iris)

# Convert to pmml
iris_lm_pmml <- pmml(iris_lm)

# Write to file
# save_pmml(iris_lm_pmml,"iris_lm.pmml")

Please note that this project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

These tools are provided as-is and without warranty or support. They do not constitute part of the Software AG product suite. Users are free to use, fork and modify them, subject to the license agreement. While Software AG welcomes contributions, we cannot guarantee to include every contribution in the master project.

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Version

Install

install.packages('pmml')

Monthly Downloads

3,435

Version

2.5.2

License

GPL-3 | file LICENSE

Issues

Pull Requests

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Repository

https://github.com/SoftwareAG/r-pmml

Homepage

https://open-source.softwareag.com/r-pmml/

Maintainer

Dmitriy Bolotov

Last Published

March 4th, 2022

Functions in pmml (2.5.2)

function_to_pmml

Convert an R expression to PMML.

Create Interval elements, most likely to add to a DataDictionary element.

Audit: artificially constructed dataset

add_output_field

Add Output nodes to a PMML object.

Add attribute values to an existing element in a given PMML file.

Modified 1984 United States Congressional Voting Records Database

add_data_field_attributes

Add attribute values to an existing DataField element in a given PMML file

file_to_xml_node

Read in a file and parse it into an object of type XMLNode.

add_data_field_children

Add 'Interval' and 'Value' child elements to a given DataField element in a given PMML file.

Generate the PMML representation for a coxph object from the package survival.

add_mining_field_attributes

Add attribute values to an existing MiningField element in a given PMML file.

Generate the PMML representation for an ada object from the package ada.

Generate the PMML representation for R objects.

Generate the PMML representation for a cv.glmnet object from the package glmnet.

Generate PMML for an iForest object from the isofor package.

Generate the PMML representation for a hclust object from the package amap.

Generate the PMML representation for an rpart object from the package rpart.

pmml.randomForest

Generate the PMML representation for a randomForest object from the package randomForest.

Generate the PMML representation for a nnet object from package nnet.

xform_discretize

Discretize a continuous variable as indicated by interval mappings in accordance with the PMML element Discretize.

Generate the PMML representation for a glm object from the package stats.

Generate the PMML representation for a gbm object from the package gbm.

make_output_nodes

Add Output nodes to a PMML object.

pmml.naiveBayes

Generate the PMML representation for a naiveBayes object from the package e1071.

Generate the PMML representation for an lm object from the package stats.

Generate the PMML representation for a multinom object from package nnet.

Generate the PMML representation for a rules or an itemset object from package arules.

Create Values element, most likely to add to a DataDictionary element.

pmml: Generate PMML for R Models

Generate PMML for a neighbr object from the neighbr package.

Generate PMML for an ARIMA object the forecast package.

Generate the PMML representation of an svm object from the e1071 package.

Save a pmml object as an external PMML file.

xform_norm_discrete

Normalize discrete values in accordance with the PMML element NormDiscrete.

rename_wrap_var

Rename a variable in the xform_wrap transform object.

Generate the PMML representation for a kmeans object from the package stats.

Add a function transformation to a xform_wrap object.

Generate the PMML representation for a ksvm object from the package kernlab.

Implement a map between discrete values in accordance with the PMML element MapValues.

pmml.xgb.Booster

Generate PMML for a xgb.Booster object from the package xgboost.

Wrap data in a data transformations object.

Normalize continuous values in accordance with the PMML element NormContinuous.

Perform a z-score normalization on continuous values in accordance with the PMML element NormContinuous.