Package: pmml 2.5.2

Dmitriy Bolotov

pmml: Generate PMML for Various Models

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").

Authors:Dmitriy Bolotov [aut, cre], Tridivesh Jena [aut], Graham Williams [aut], Wen-Ching Lin [aut], Michael Hahsler [aut], Hemant Ishwaran [aut], Udaya B. Kogalur [aut], Rajarshi Guha [aut], Software AG [cph]

pmml_2.5.2.tar.gz
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pmml.pdf |pmml.html
pmml/json (API)
NEWS

# Install 'pmml' in R:
install.packages('pmml', repos = c('https://cumulocity-iot.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/softwareag/r-pmml/issues

Datasets:
  • audit - Audit: artificially constructed dataset
  • houseVotes84 - Modified 1984 United States Congressional Voting Records Database

On CRAN:

machine-learningpmmlzementis

7.97 score 20 stars 1 packages 580 scripts 2.7k downloads 41 exports 9 dependencies

Last updated 3 years agofrom:9daa76510c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 29 2024
R-4.5-winOKOct 29 2024
R-4.5-linuxOKOct 29 2024
R-4.4-winOKOct 29 2024
R-4.4-macOKOct 29 2024
R-4.3-winOKOct 29 2024
R-4.3-macOKOct 29 2024

Exports:add_attributesadd_data_field_attributesadd_data_field_childrenadd_mining_field_attributesadd_output_fieldfile_to_xml_nodefunction_to_pmmlmake_intervalsmake_output_nodesmake_valuespmmlpmml.adapmml.ARIMApmml.coxphpmml.cv.glmnetpmml.gbmpmml.glmpmml.hclustpmml.iForestpmml.itemsetspmml.kmeanspmml.ksvmpmml.lmpmml.multinompmml.naiveBayespmml.neighbrpmml.nnetpmml.randomForestpmml.rpartpmml.rulespmml.svmpmml.xgb.Boosterrename_wrap_varsave_pmmlxform_discretizexform_functionxform_mapxform_min_maxxform_norm_discretexform_wrapxform_z_score

Dependencies:cligluelifecyclemagrittrrlangstringistringrvctrsXML

Introduction to xform_function

Rendered fromxform_function.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2021-04-09
Started: 2019-05-29

Supported Packages and Additional Functions

Rendered frompackages_and_functions.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2022-03-03
Started: 2019-05-29

Readme and manuals

Help Manual

Help pageTopics
Add attribute values to an existing element in a given PMML file.add_attributes
Add attribute values to an existing DataField element in a given PMML fileadd_data_field_attributes
Add 'Interval' and 'Value' child elements to a given DataField element in a given PMML file.add_data_field_children
Add attribute values to an existing MiningField element in a given PMML file.add_mining_field_attributes
Add Output nodes to a PMML object.add_output_field
Audit: artificially constructed datasetaudit
Read in a file and parse it into an object of type XMLNode.file_to_xml_node
Convert an R expression to PMML.function_to_pmml
Modified 1984 United States Congressional Voting Records DatabasehouseVotes84
Create Interval elements, most likely to add to a DataDictionary element.make_intervals
Add Output nodes to a PMML object.make_output_nodes
Create Values element, most likely to add to a DataDictionary element.make_values
Generate the PMML representation for R objects.pmml
Generate the PMML representation for an ada object from the package 'ada'.pmml.ada
Generate PMML for an ARIMA object the *forecast* package.pmml.ARIMA
Generate the PMML representation for a coxph object from the package 'survival'.pmml.coxph
Generate the PMML representation for a cv.glmnet object from the package 'glmnet'.pmml.cv.glmnet
Generate the PMML representation for a gbm object from the package 'gbm'.pmml.gbm
Generate the PMML representation for a glm object from the package 'stats'.pmml.glm
Generate the PMML representation for a hclust object from the package 'amap'.pmml.hclust
Generate PMML for an iForest object from the *isofor* package.pmml.iForest
Generate the PMML representation for a kmeans object from the package 'stats'.pmml.kmeans
Generate the PMML representation for a ksvm object from the package 'kernlab'.pmml.ksvm
Generate the PMML representation for an lm object from the package 'stats'.pmml.lm
Generate the PMML representation for a multinom object from package 'nnet'.pmml.multinom
Generate the PMML representation for a naiveBayes object from the package 'e1071'.pmml.naiveBayes
Generate PMML for a neighbr object from the *neighbr* package.pmml.neighbr
Generate the PMML representation for a nnet object from package 'nnet'.pmml.nnet
Generate the PMML representation for a randomForest object from the package 'randomForest'.pmml.randomForest
Generate the PMML representation for an rpart object from the package 'rpart'.pmml.rpart
Generate the PMML representation for a rules or an itemset object from package 'arules'.pmml.itemsets pmml.rules
Generate the PMML representation of an svm object from the 'e1071' package.pmml.svm
Generate PMML for a xgb.Booster object from the package 'xgboost'.pmml.xgb.Booster
Rename a variable in the xform_wrap transform object.rename_wrap_var
Save a pmml object as an external PMML file.save_pmml
Discretize a continuous variable as indicated by interval mappings in accordance with the PMML element *Discretize*.xform_discretize
Add a function transformation to a xform_wrap object.xform_function
Implement a map between discrete values in accordance with the PMML element *MapValues*.xform_map
Normalize continuous values in accordance with the PMML element *NormContinuous*.xform_min_max
Normalize discrete values in accordance with the PMML element *NormDiscrete*.xform_norm_discrete
Wrap data in a data transformations object.xform_wrap
Perform a z-score normalization on continuous values in accordance with the PMML element *NormContinuous*.xform_z_score