Module datarush.analytics

Package com.pervasive.datarush.analytics.cluster

Class ClusterPredictor

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.analytics.util.AbstractPredictor

com.pervasive.datarush.analytics.cluster.ClusterPredictor

All Implemented Interfaces:

LogicalOperator

public final class ClusterPredictor
extends AbstractPredictor

Assigns input data to clusters based on the provided PMML Clustering Model. The explicit cluster IDs will be used for the assignment, if the model provides any. Otherwise, the implicit 1-based index, indicating the position in which each cluster appears in the model will be used as ID. The input data must contain the same fields as the training data that was used to build the model (in the PMML model: clustering fields with the attribute "isCenterField" set to "true") and these fields must be of type double, float, long or int. The resulting assignments will be part of the output alongside with the original input data.

Constructor Summary

Constructors

Constructor	Description
ClusterPredictor()

Method Summary

Modifier and Type	Method	Description
protected void	execute(PMMLModel model, RecordValued input, ScalarSettable[] predictedFields)	Called to perform prediction.
RecordPort	getOutput()	Returns a record port consisting of the input plus the assigned cluster IDs.
String	getWinnerFieldName()	Gets the name of the winner field in the output.
protected RecordTokenType	predictedType(PMMLModelSpec modelSpec)	Given the model spec, returns the predicted type.
void	setWinnerFieldName(String winnerFieldName)	Sets the name of the winner field in the output.

Methods inherited from class com.pervasive.datarush.analytics.util.AbstractPredictor

computeMetadata, execute, getInput, getModel, pushPrediction, stepNext

Methods inherited from class com.pervasive.datarush.operators.ExecutableOperator

cloneForExecution, getNumInputCopies, getPortSettings, handleInactiveOutput

Methods inherited from class com.pervasive.datarush.operators.AbstractLogicalOperator

disableParallelism, getInputPorts, getOutputPorts, newInput, newInput, newOutput, newRecordInput, newRecordInput, newRecordOutput, notifyError

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ClusterPredictor

public ClusterPredictor()

Method Detail

getWinnerFieldName

public String getWinnerFieldName()

Gets the name of the winner field in the output. This is "winner" by-default. For every input row, this field will contain the ID of the cluster, that row was assigned to.

Returns:

the name of the winner field in the output

setWinnerFieldName

public void setWinnerFieldName(String winnerFieldName)

Sets the name of the winner field in the output. This is "winner" by-default. For every input row, this field will contain the ID of the cluster, that row was assigned to.

Parameters:

winnerFieldName - the name of the winner field in the output.

getOutput

public RecordPort getOutput()

Returns a record port consisting of the input plus the assigned cluster IDs. If the model provides cluster IDs, these explicit IDs will be used in the output. Otherwise, the implicit 1-based index, indicating the position in which each cluster appears in the model will be used as ID. The name of the field containing the resulting assignments is configurable via the property winnerFieldName. The default name is "winner".

Overrides:

getOutput in class AbstractPredictor

Returns:

a record flow of original values and their cluster assignments.

predictedType

protected RecordTokenType predictedType(PMMLModelSpec modelSpec)

Description copied from class: AbstractPredictor

Given the model spec, returns the predicted type. This should not include the input type ( the input is automatically prepended to the type that is returned )

Specified by:

predictedType in class AbstractPredictor

Parameters:

modelSpec - the model metadata

Returns:

the predicted type

execute

protected void execute(PMMLModel model,
                       RecordValued input,
                       ScalarSettable[] predictedFields)

Description copied from class: AbstractPredictor

Called to perform prediction. Subclasses are expected to loop over the input by calling AbstractPredictor.stepNext(). For each row of input, subclasses should first set the predicted values in the predictedFields array and then invoke AbstractPredictor.pushPrediction(). Subclasses should not invoke pushEndOfData since that is automatically handled by the base class.

Specified by:

execute in class AbstractPredictor

Parameters:

model - The input PMML model

input - The input data

predictedFields - An array of fields that reference the predicted field locations. The array positionally corresponds to the type returned by AbstractPredictor.predictedType(PMMLModelSpec).