Data Mining Group - PMML Powered

PMML Powered

Company / Project	Software	PMML Producer	PMML Consumer	Supported Model Type
	ACTICO Rules		PMML 3.0 through 4.2	Decision Trees
	Alpine	PMML 4.1		Regression Models (Linear and Logistic) Naïve Bayes K-Means Alpine Forest SVM
	PMML scoring library for Scala (PMML4S)		PMML 2.0 through 4.4	Anomaly Detection Models Association Rules Cluster Models General Regression Mining Models Naïve Bayes Neural Networks k-Nearest Neighbors Regression Ruleset Scorecards Support Vector Machines Trees
	Python PMML scoring library (PyPMML)		PMML 2.0 through 4.4	Anomaly Detection Models Association Rules Cluster Models General Regression Mining Models Naïve Bayes Neural Networks k-Nearest Neighbors Regression Ruleset Scorecards Support Vector Machines Trees
	Serving PMML with both HTTP and gRPC endpoints (AI-Serving)		PMML 2.0 through 4.4	Anomaly Detection Models Association Rules Cluster Models General Regression Mining Models Naïve Bayes Neural Networks k-Nearest Neighbors Regression Ruleset Scorecards Support Vector Machines Trees
	BigML Public API	PMML 4.1		Decision Trees (classification and regression)
	KnowledgeSTUDIO	PMML 3.2	PMML 3.2 through 4.2	Decision Trees Regression Models (Linear and Logistic) Neural Networks Clustering Models Rule Set Models (Scorecards)
	KnowledgeSEEKER	PMML 3.2	PMML 3.2 through 4.2	Decision Trees
	Model Integration Tool ™	PMML 4.2	PMML 4.2	Scorecards Regression Models (Linear and Logistic) Segmented Scorecard Models Decision Tree (Ensemble)
	Strategy Tree Optimization	PMML 3.0, 3.1	PMML 3.0, 3.1	Decision Tree
	PowerCurve™ Strategy Management	PMML 3.0, 3.1, 4.0, 4.1	PMML 3.0, 3.1, 4.0, 4.1	Decision Tree
	PowerCurve™ Strategy Management		PMML 3.0, 3.1, 4.0, 4.1	Regression Model
	Model Builder	PMML 4.1, 3.2, 3.0		Scorecards Regression Models (Linear and Logistic) Neural Networks Decision Trees Segmented Scorecard Models Boosted Tree Ensembles All R PMML produced models (see R/Rattle entry below)
	Analytic Modeler Scorecard	PMML 4.1		Scorecards Boosted Tree Ensembles
	Analytic Modeler Scorecard Professional	PMML 4.2, 3.2		Scorecards

	Decision Optimizer	PMML 3.2	PMML 3.2	Consumes: Scorecards Regression Models (Linear and Logistic) Neural Networks Decision Trees Produces: Decision Trees
	Blaze Advisor		PMML 3.2, 4.2	Scorecards Regression Models (Linear and Logistic) Neural Networks Decision Trees Random Forests
	Model Executor for PMML		PMML 2.0 through 4.2	Cluster General Regression Naïve Bayes Neural Networks Regression Ruleset Scorecard Trees Vector Machines
	Decision Management Platform Streaming		PMML 2.0 through 4.2	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining
	Strategy Director		PMML 3.2, 4.2	Scorecards Regression Models (Linear and Logistic)
	Financial Crime Risk Management Platform		PMML 2.0 through 4.2	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining
	XLMiner® SDK, Analytic Solver® Data Mining, AnalyticSolver.com	PMML 4.2	PMML 4.2	Regression Models (Linear and Logistic) Decision Trees Neural Networks k-Nearest Neighbors Naïve Bayes Random Forest Time Series Association Rules (Producer Only) Transformations Multiple Models
	DataView360® Decision Engine		PMML 3.0 through 4.3	General Regression Regression Neural Network Ruleset Trees Scorecards Vector Machine Multiple Models: Model Composition, Ensembles and Segmentation
	IBM SPSS Statistics 21	PMML4.0	PMML2.0 through 4.0	Clustering Models Decision Trees General Regression MiningModel Neural Networks Time Series Naïve Bayes (produced only by SPSS Statistics Server) Also consumes Ruleset, Regression, and Support Vector Machine Models
	IBM SPSS Statistics 22	PMML4.1	PMML2.0 through 4.1	Clustering Models Decision Trees General Regression k-Nearest Neighbors Mining Model Neural Networks Time Series Naïve Bayes (produced only by SPSS Statistics Server) Also consumes Ruleset, Regression, and Support Vector Machine Models
	IBM SPSS Statistics 23	PMML4.1	PMML2.0 through 4.1	Association Model (only produced) Clustering Models Decision Trees General Regression k-Nearest Neighbors Mining Model Neural Networks Time Series Naïve Bayes (produced only by SPSS Statistics Server) Also consumes Ruleset, Regression, and Support Vector Machine Models
	IBM SPSS Modeler 15	PMML4.0	PMML2.0 through 4.0	Produces: Association Model Clustering Models Decision Trees Mining Model Naïve Bayes Neural Networks Regression & General Regression Models Ruleset Models Support Vector Machines Consumes (scores): all of the above except Association, and Mining Model.
	IBM SPSS Modeler 16	PMML4.1	PMML2.0 through 4.1	Produces: Association Model Clustering Models Decision Trees k-Nearest Neighbors Mining Model Naïve Bayes Neural Networks Regression & General Regression Models Ruleset Models Support Vector Machines Consumes (scores): all of the above except Association, and Mining Model.
	IBM SPSS Modeler 17	PMML4.1	PMML2.0 through 4.1	Produces: Association Model Clustering Models Decision Trees k-Nearest Neighbors Mining Model Naïve Bayes Neural Networks Regression & General Regression Models Ruleset Models Support Vector Machines Consumes (scores): all of the above except Association.
	IBM SPSS Collaboration and Deployment Services v. 5.0		PMML2.0 through 4.0	Clustering Models Decision Trees Naïve Bayes Neural Networks Regression & General Regression Ruleset Models Support Vector Machines
	IBM SPSS Collaboration and Deployment Services v. 6.0		PMML2.0 through 4.1	Clustering Models Decision Trees Nearest Neighbors Naïve Bayes Neural Networks Regression & General Regression Ruleset Models Support Vector Machines
	IBM SPSS Collaboration and Deployment Services v. 7.0		PMML2.0 through 4.1	Clustering Models Decision Trees Nearest Neighbors Naïve Bayes Neural Networks Regression & General Regression Ruleset Models Support Vector Machines
	IBM Netezza Analytics v3.0	PMML 4.0		Association Rules Clustering Models (center-based and distribution-based) Decision Tree Models Naive Bayes
	IBM InfoSphere Warehouse V9.7 IBM InfoSphere Warehouse V10.1 IBM DB2 Advanced Enterprise Server Edition V10.5 IBM DB2 Advanced Workgroup Server Edition V10.5	PMML 3.2	PMML 2.0 through 3.2	Association Rules Models Sequence Models Naïve Bayes Models Logistic Regression Models
		PMML 3.0		Clustering Models (center and distribution based) Regression Models Decision Trees
			PMML 2.0 through 3.0	Clustering Models (center and distribution based) Regression Models Decision Trees Neural Networks
	InterSystems IRIS Data Platform		PMML 4.0 through 4.3	Clustering Models Naïve Bayes Models Regression & General Regression Neural Networks Mining Models & Segmentation Decision Rules & Trees Support Vector Machines Text models
	KNIME 2.10	PMML 4.2	PMML 4.2	Neural Networks Regression and General Regression Models Clustering Models Decision Trees Naïve Bayes Rule Set Editor Rule Set Predictor Support Vector Machines including support for Transformation elements Model Ensembles And support for Transformation elements
	KNIME 2.10 with R extension	PMML 4.1	PMML 4.1	All R PMML produced models (see R/Rattle entry below) that are compatible to PMML 4.1
KXEN	Analytic Framework 4.0.10, 5.0.7 and 5.1.2	PMML 3.2		Regression Models, Clustering Models, Mining Models
	Kamanja		PMML 4.0 to 4.2	Assocation rules (Association) Cluster model (Clustering) General regression (Regression, Cox regression, Classification) k-Nearest neighbors (Regression, Classification, Clustering) Naive Bayes (Classification) Neural network (Regression, Classification (Except for the radialBasis value of the activationFunction attribute)) Regression (Regression, Classification) Rule set (Classification) Scorecard (Regression) Tree model (Classification) Support Vector Machine (SVM) (Regression, Classification) Ensemble model (Regression, Classification, Clustering)
Microsoft	SQL Server	PMML 2.1		Decision Trees (Classification), Clustering Models (Distribution-based)
	MicroStrategy Data Mining Services Versions 8.0 and above	PMML 3.0, 3.1, 4.0	PMML 2.0, 2.1, 3.0,3.1, 3.2, 4.0	Regression Models (Consumer & Producer) Decision Trees (Consumer & Producer) Mining Models (Consumer & Producer) Clustering Models (Consumer & Producer) Neural Network Models (Consumer Only) General Regression Models (Consumer Only) Support Vector Machine Models (Consumer Only) Rule Set Models (Consumer Only) Association Rules (Consumer & Producer) Time Series Models (Consumer & Producer)
	Lily		PMML 2.0 through 4.2	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining
	PyMC3.BN	PMML 4.3	PMML 4.3	Bayesian Networks
	Matlab GP	PMML 4.3	PMML 4.3	Gaussian Process Regression
	Pmml-scoring-engine		PMML 4.3	Gaussian Process Regression
	Augustus 0.4x	PMML 4.0	PMML 4.0	Decision Trees Regression Naïve Bayes Baseline (With Segmentation on all of the above)
	Augustus 0.5x	PMML 4.1	PMML 4.1	Baseline Clusters Naïve Bayes Regression RuleSet Trees (With Segmentation on all of the above)
	Augustus 0.6x	PMML 4.1	PMML 4.1	Baseline Clusters Trees (With Segmentation on all of the above)
	Java Class Model API for PMML (JPMML-Model)	PMML 3.0 through 4.2		All model types
	Java Evaluator API for PMML (JPMML-Evaluator)		PMML 3.0 through 4.2	Association Rules Decision Trees Clustering General Regression Mining Model Naïve Bayes k-NN Neural Network Regression Rule Sets Scorecards SVM
	Openscoring REST API		PMML 3.0 through 4.2	Association Rules Decision Trees Clustering General Regression Mining Model Naïve Bayes k-NN Neural Network Regression Rule Sets Scorecards SVM
	Signal Hub 2.7	PMML 4.2	PMML 3.0 through 4.2	Produces Decision Trees Clustering Regression Models Naïve Bayes Support Vector Machines Neural Networks Consumes Association Rules Decision Trees Clustering General Regression Mining Model Naïve Bayes Neural Networks Regression Models Rule Sets Scorecards Support Vector Machines
	Pega Platform 7.3.1		PMML 3.0 through 4.3	Cluster model General regression Mining (multiple/ensemble) model Neural Network k-Nearest Neighbors Naïve Bayes Ruleset Regression Support Vector Machine Scorecard Tree
Pervasive DataRush	Pervasive DataRush V5.0	PMML 3.2	PMML 3.2	Decision Trees (Consumer & Producer) Regression Models (Consumer & Producer) Clustering Models (kmeans Center-Based) Association Rules (Producer) Naïve Bayes (Consumer & Producer)
	PMML Connexion		PMML 2.0 through 4.0	Decision Trees Support Vector Machines Neural Networks Regression and General Regression Clustering Models Naiive Bayes
	RapidMiner with PMML Extension	PMML 3.2, 4.0		Linear Regression Logistic Regression Models Decision Trees Rules K-Medoids K-Means Naïve Bayes
R	PMML package	PMML 4.3		kNN Mining Models Regression Models General Regression Models (including Cox) Neural Networks Decision Trees Clustering Models Association Rules Support Vector Machines Multinomial Logistic Regression Random Forest Random Survival Forest Naïve Bayes Classifiers And support for merging of Transformation elements
R	PMMLTransformations Package	PMML 4.3		Transformations
Salford Systems	CART 6.0	PMML 3.1		Decision Trees Composition
	TreeNet 2.0 Pro	3.1		Composition
	Mars 3.0	3.2		Simple Regression (uses transformations and user-defined functions to implement basis functions)
SAND Technology	SAND CDBMS V6.1 PMML extension		PMML 3.1, 3.2	Association Rules Clustering Models Regression Models Neural Networks Naïve Bayes Support Vector Machines Ruleset Model Decision Trees
	SAS Enterprise Miner	PMML 2.1 (EM 5.1) PMML 3.1 (EM 5.3) PMML 4.0 (EM 7.1) PMML 4.1 (EM 12.3 and 13.1)		Linear Regression Logistic Regression Decision Trees Neural Networks Clustering Association Rules
	SAS Base 9.3M2		PMML 4.0	Clustering Neural Networks Regression Tree
	SAS Base 9.40		PMML 4.1	Clustering Neural Networks Regression Tree Scorecard General Regression
	SAS Base V9.40M1		PMML 4.1	Clustering Neural Networks Regression Tree Scorecard General Regression Naïve Bayes Support Vector Machine Time Series
	Apama Streaming Analytics		PMML 2.0 through 4.2	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining
	Apache Spark	PMML 4.2		Clustering Models K-Means Regression Models (Linear, Ridge, Binary Logistic) Lasso Model SVM
	Sparkling Logic SMARTS™		PMML 4.2	Neural Networks Support Vector Machines Trees / Decision Trees Naïve Bayes Regression (Linear, Logistic, Multinomial) & General Regression Clustering Models Ruleset Models Scorecards Mining Models (incl. Random Forest) Transformations, Pre-post-processing
	Teradata Vantage™ - Bring Your Own Model (BYOM)		PMML 2.0 through 4.4	Anomaly Detection Association Rules Cluster General regression k-Nearest Neighbors Naive Bayes Neural Network Regression Ruleset Scorecard Random Forest Decision Tree Vector Machine Multiple Models
	TIBCO Spotfire 6.5	PMML 4.1		All R PMML produced models (see R/Rattle entry above)
	TIBCO Enterprise Runtime for R 2.5	PMML 4.1		All R PMML produced models (see R/Rattle entry above)
	Trisotech Digital Automation Suite (DAS)		PMML 3.0 through 4.4	Association rules Cluster model General regression Naive Bayes k-Nearest neighbors Neural network Regression Rule set Scorecard Support Vector Machine Tree model Ensemble model
Weka (Pentaho)	Weka		PMML 3.2	Regression and General Regression Neural Networks Rule Set Models Decision Trees
	Py2PMML Converter	PMML 4.3		Decision Trees Random Forest Models Clustering Regression Models
	Zementis Predictive Analytics Engine		PMML 2.0 through 4.3	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining
	Universal PMML Plug-in for Hadoop		PMML 2.0 through 4.3	Decision Trees Support Vector Machines Mining Models Neural Networks Regression & General Regression Clustering Models Naïve Bayes Ruleset Models Association Rules Scorecards Pre- and post-processing Text Mining

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