| Package | Description | 
|---|---|
| com.pervasive.datarush.analytics.arm | 
 Provides common classes for Association Rule Mining (ARM). 
 | 
| com.pervasive.datarush.analytics.cluster | 
 Provides base PMML for clustering models. 
 | 
| com.pervasive.datarush.analytics.decisiontree | 
 Provides PMML model classes for decision trees. 
 | 
| com.pervasive.datarush.analytics.decisiontree.predictor | 
 Provides the decision tree predictor operator and associated classes. 
 | 
| com.pervasive.datarush.analytics.naivebayes | 
 Provides PMML model classes for Naive Bayes. 
 | 
| com.pervasive.datarush.analytics.naivebayes.predictor | 
 Provides an implementation of a Naive Bayes predictor. 
 | 
| com.pervasive.datarush.analytics.pmml | 
 Provides shared and base classes for PMML model representation of Analytics algorithms. 
 | 
| com.pervasive.datarush.analytics.regression | 
 Provides utility, PMML and other classes for shared use by regression related entities. 
 | 
| com.pervasive.datarush.analytics.stats | 
 Provides various statistics, Data Summarizer, and Data Quality Analyzer. 
 | 
| com.pervasive.datarush.analytics.svm | 
 Provides PMML model classes for SVM. 
 | 
| com.pervasive.datarush.analytics.svm.predictor | 
 Provides an implementation of an SVM predictor. 
 | 
| com.pervasive.datarush.analytics.util | 
 Provides some (internal) utility classes for Analytics. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
static PMMLModelSpec | 
MetadataHelper.createPMMLSpec(RecordTokenType inputType,
              String txnFieldName,
              String itemFieldName)
Build the PMML model specification for an ARM model given the transaction field and item field names. 
 | 
| Constructor and Description | 
|---|
PMMLAssociationModel(PMMLModelSpec spec)
Construct a  
PMMLAssociationObject from the given specification. | 
| Modifier and Type | Method and Description | 
|---|---|
static PMMLClusteringModel.Builder | 
PMMLClusteringModel.builder(PMMLModelSpec spec,
       ModelClass modelClass,
       ComparisonMeasure comparisonMeasure,
       Cluster[] clusters)
Creates a builder that builds  
PMMLClusteringModel
 instances with the provided model specification, model class,
 comparison measure and clusters. | 
protected RecordTokenType | 
ClusterPredictor.predictedType(PMMLModelSpec modelSpec)  | 
| Constructor and Description | 
|---|
PMMLTreeModel(PMMLModelSpec modelSpec)
Create a PMMLTreeModel for the given spec. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected RecordTokenType | 
DecisionTreePredictor.predictedType(PMMLModelSpec modelSpec)  | 
| Constructor and Description | 
|---|
PMMLNaiveBayesModel(PMMLModelSpec modelSpec)
Create a PMMLNaiveBayesModel for the given spec. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected RecordTokenType | 
NaiveBayesPredictor.predictedType(PMMLModelSpec spec)  | 
| Modifier and Type | Method and Description | 
|---|---|
static PMMLModelSpec | 
PMMLModelSpec.forAll(RecordTokenType inputType,
      String... targetColumns)
Convenience method to create a model spec where the learning columns
 are all input columns minus the target columns 
 | 
static PMMLModelSpec | 
PMMLModelSpec.forSelected(RecordTokenType inputType,
           List<String> selectedColumns,
           String... targetColumns)
Convenience method to create a model spec where the learning columns
 are the specified selected columns minus the set of target columns. 
 | 
PMMLModelSpec | 
PMMLModel.getModelSpec()
Returns the meta-information associated with this PMML model 
 | 
PMMLModelSpec | 
PMMLPort.Metadata.getPMMLModelSpec()
Returns the underlying PMML model metadata 
 | 
PMMLModelSpec | 
PMMLPort.getPMMLModelSpec(MetadataContext ctx)
Getter to be used to set the PMMLModelSpec for a PMMLPort 
 | 
| Modifier and Type | Method and Description | 
|---|---|
void | 
PMMLPort.setPMMLModelSpec(MetadataCalculationContext ctx,
                PMMLModelSpec spec)
Setter to be used to set the PMMLModelSpec for PMML ports. 
 | 
| Constructor and Description | 
|---|
Metadata(PMMLModelSpec pmmlModelSpec)
Creates a new port metadata 
 | 
PMMLModel(PMMLModelSpec objectSpec)
Create a model, specifying a model spec. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected RecordTokenType | 
RegressionPredictor.predictedType(PMMLModelSpec modelSpec)  | 
protected RecordTokenType | 
LogisticRegressionPredictor.predictedType(PMMLModelSpec modelSpec)  | 
| Constructor and Description | 
|---|
AbstractPMMLRegressionModel(PMMLModelSpec objectSpec)  | 
PMMLRegressionClassificationModel(PMMLModelSpec objectSpec)  | 
PMMLRegressionModel(PMMLModelSpec objectSpec)
Construct the PMML model from a model specification. 
 | 
| Constructor and Description | 
|---|
PMMLSummaryStatisticsModel(PMMLModelSpec modelSpec)
Create a PMMLSummaryStatisticsModel for the given spec. 
 | 
| Constructor and Description | 
|---|
PMMLSupportVectorMachineModel(PMMLModelSpec modelSpec)
Create a PMMLSupportVectorMachineModel for the given spec. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected RecordTokenType | 
SVMPredictor.predictedType(PMMLModelSpec modelSpec)  | 
| Modifier and Type | Method and Description | 
|---|---|
PMMLModelSpec | 
MixedTypeMetadataHelper.getPmmlSpec()  | 
| Modifier and Type | Method and Description | 
|---|---|
protected abstract RecordTokenType | 
AbstractPredictor.predictedType(PMMLModelSpec modelSpec)
Given the model spec, returns the predicted type. 
 | 
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