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JPMML class model evaluator
/*
* Copyright (c) 2013 Villu Ruusmann
*
* This file is part of JPMML-Evaluator
*
* JPMML-Evaluator is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* JPMML-Evaluator is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with JPMML-Evaluator. If not, see .
*/
package org.jpmml.evaluator;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Comparator;
import java.util.List;
import java.util.Map;
import com.google.common.base.Joiner;
import com.google.common.collect.Ordering;
import org.dmg.pmml.DataField;
import org.dmg.pmml.DataType;
import org.dmg.pmml.Model;
import org.dmg.pmml.OpType;
import org.dmg.pmml.Output;
import org.dmg.pmml.OutputField;
import org.dmg.pmml.PMMLAttributes;
import org.dmg.pmml.ResultFeature;
import org.dmg.pmml.Target;
import org.dmg.pmml.TargetValue;
import org.dmg.pmml.Value;
import org.dmg.pmml.association.AssociationRule;
import org.dmg.pmml.association.Item;
import org.dmg.pmml.association.ItemRef;
import org.dmg.pmml.association.Itemset;
import org.dmg.pmml.mining.MiningModel;
import org.dmg.pmml.mining.Segmentation;
import org.jpmml.evaluator.mining.MiningModelEvaluationContext;
import org.jpmml.evaluator.mining.MiningModelUtil;
import org.jpmml.evaluator.mining.SegmentResult;
import org.jpmml.model.InvalidAttributeException;
import org.jpmml.model.InvalidElementException;
import org.jpmml.model.MisplacedAttributeException;
import org.jpmml.model.MissingAttributeException;
import org.jpmml.model.UnsupportedAttributeException;
import org.jpmml.model.UnsupportedElementException;
public class OutputUtil {
private OutputUtil(){
}
/**
*
* Evaluates the {@link Output} element.
*
*
* @param predictions A map of {@link Evaluator#getTargetFields() target field} values.
*
* @return A map of {@link Evaluator#getTargetFields() target field} values together with {@link Evaluator#getOutputFields() output field} values.
*/
static
public Map evaluate(Map predictions, ModelEvaluationContext context){
ModelEvaluator> modelEvaluator = context.getModelEvaluator();
Model model = modelEvaluator.getModel();
Output output = model.getOutput();
if(output == null || !output.hasOutputFields()){
return predictions;
}
OutputMap result = new OutputMap(predictions);
OutputFilter outputFilter = modelEvaluator.ensureOutputFilter();
List outputFields = output.getOutputFields();
outputFields:
for(int i = 0, max = outputFields.size(); i < max; i++){
OutputField outputField = outputFields.get(i);
String targetFieldName = outputField.getTargetField();
Object targetValue = null;
boolean requireTargetValue;
ResultFeature resultFeature = outputField.getResultFeature();
switch(resultFeature){
case TRANSFORMED_VALUE:
case DECISION:
case WARNING:
requireTargetValue = false;
break;
default:
requireTargetValue = true;
break;
}
String segmentId = outputField.getSegmentId();
SegmentResult segmentPredictions;
// Load the target value of the specified segment
if(segmentId != null){
if(!(model instanceof MiningModel)){
throw new MisplacedAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_SEGMENTID, segmentId);
}
MiningModelEvaluationContext miningModelContext = (MiningModelEvaluationContext)context;
segmentPredictions = miningModelContext.getResult(segmentId);
// "If there is no Segment matching segmentId or if the predicate of the matching Segment evaluated to false, then the result delivered by this OutputField is missing"
if(segmentPredictions == null){
continue outputFields;
} // End if
if(requireTargetValue){
if(targetFieldName != null){
if(!segmentPredictions.containsKey(targetFieldName)){
throw new MissingFieldValueException(targetFieldName, outputField);
}
targetValue = segmentPredictions.get(targetFieldName);
} else
{
targetValue = segmentPredictions.getTargetValue();
}
}
} else
// Load the target value
{
segmentPredictions = null;
targetValue:
if(requireTargetValue){
if(model instanceof MiningModel){
MiningModel miningModel = (MiningModel)model;
switch(resultFeature){
case ENTITY_ID:
{
if(targetFieldName != null){
throw new MisplacedAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_TARGETFIELD, targetFieldName);
}
// "Result feature entityId returns the id of the winning segment"
targetValue = TypeUtil.cast(HasEntityId.class, predictions);
break targetValue;
}
default:
{
if(targetFieldName != null){
break;
}
Segmentation segmentation = miningModel.requireSegmentation();
SegmentResult segmentResult = MiningModelUtil.asSegmentResult(segmentation.requireMultipleModelMethod(), predictions);
if(segmentResult != null){
targetValue = segmentResult.getTargetValue();
break targetValue;
}
}
break;
}
} // End if
if(targetFieldName == null){
targetFieldName = modelEvaluator.getTargetName();
} // End if
if(!predictions.containsKey(targetFieldName)){
throw new MissingFieldValueException(targetFieldName, outputField);
}
targetValue = predictions.get(targetFieldName);
}
}
// "If the target value is missing, then the result delivered by this OutputField is missing"
if(requireTargetValue && targetValue == null){
continue outputFields;
}
Object value;
// Perform the requested computation on the target value
switch(resultFeature){
case PREDICTED_VALUE:
{
value = getPredictedValue(targetValue);
}
break;
case PREDICTED_DISPLAY_VALUE:
{
if(segmentId != null){
throw new UnsupportedElementException(outputField);
}
TargetField targetField = modelEvaluator.findTargetField(targetFieldName);
if(targetField == null){
throw new MissingFieldException(targetFieldName, outputField);
}
value = getPredictedDisplayValue(targetValue, targetField);
}
break;
case TRANSFORMED_VALUE:
case DECISION:
{
if(segmentId != null){
Object name = outputField.requireValue();
value = segmentPredictions.get(TypeUtil.format(name));
break;
}
value = FieldValueUtil.getValue(ExpressionUtil.evaluateExpressionContainer(outputField, context));
}
break;
case PROBABILITY:
{
value = getProbability(targetValue, outputField);
}
break;
case CONFIDENCE:
{
if(targetValue instanceof HasRuleValues){
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.CONFIDENCE);
break;
}
value = getConfidence(targetValue, outputField);
}
break;
case RESIDUAL:
{
if(segmentId != null){
throw new UnsupportedElementException(outputField);
}
FieldValue expectedTargetValue = context.evaluate(targetFieldName);
if(FieldValueUtil.isMissing(expectedTargetValue)){
throw new MissingFieldValueException(targetFieldName, outputField);
}
TargetField targetField = modelEvaluator.findTargetField(targetFieldName);
if(targetField == null){
throw new MissingFieldException(targetFieldName, outputField);
}
OpType opType = targetField.getOpType();
switch(opType){
case CONTINUOUS:
value = getContinuousResidual(targetValue, expectedTargetValue);
break;
case CATEGORICAL:
case ORDINAL:
value = getDiscreteResidual(targetValue, expectedTargetValue);
break;
default:
throw new InvalidElementException(outputField);
}
}
break;
case CLUSTER_ID:
{
value = getClusterId(targetValue);
}
break;
case ENTITY_ID:
{
if(targetValue instanceof HasRuleValues){
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.RULE_ID);
break;
}
value = getEntityId(targetValue, outputField);
}
break;
case AFFINITY:
{
value = getAffinity(targetValue, outputField);
}
break;
case CLUSTER_AFFINITY:
case ENTITY_AFFINITY:
{
Object entityId = outputField.getValue();
// Select the specified entity instead of the winning entity
if(entityId != null){
value = getAffinity(targetValue, outputField);
break;
}
value = getEntityAffinity(targetValue);
}
break;
case REASON_CODE:
{
value = getReasonCode(targetValue, outputField);
}
break;
case RULE_VALUE:
{
value = getRuleValue(targetValue, outputField);
}
break;
case ANTECEDENT:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.ANTECEDENT);
}
break;
case CONSEQUENT:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.CONSEQUENT);
}
break;
case RULE:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.RULE);
}
break;
case RULE_ID:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.RULE_ID);
}
break;
case SUPPORT:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.SUPPORT);
}
break;
case LIFT:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.LIFT);
}
break;
case LEVERAGE:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.LEVERAGE);
}
break;
case REPORT:
{
String reportFieldName = outputField.getReportField();
if(reportFieldName == null){
throw new MissingAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_REPORTFIELD);
}
OutputField reportOutputField = modelEvaluator.getOutputField(reportFieldName);
if(reportOutputField == null){
throw new MissingFieldException(reportFieldName);
}
value = getReport(targetValue, reportOutputField);
}
break;
case WARNING:
{
value = context.getWarnings();
}
break;
default:
throw new UnsupportedAttributeException(outputField, resultFeature);
}
String name = outputField.requireName();
TypeInfo typeInfo = new TypeInfo(){
@Override
public OpType getOpType(){
OpType opType = outputField.getOpType();
if(opType == null){
DataType dataType = getDataType();
opType = TypeUtil.getOpType(dataType);
}
return opType;
}
@Override
public DataType getDataType(){
DataType dataType = outputField.getDataType();
if(dataType == null){
if(value instanceof Collection){
Collection> values = (Collection>)value;
dataType = TypeUtil.getDataType(values);
} else
{
dataType = TypeUtil.getDataType(value);
}
}
return dataType;
}
@Override
public List> getOrdering(){
List> ordering = FieldUtil.getValidValues(outputField);
return ordering;
}
};
FieldValue outputValue = FieldValueUtil.create(typeInfo, value);
// The result of one output field becomes available to other output fields
context.declare(name, outputValue);
if(outputFilter.test(outputField)){
result.putPublic(name, FieldValueUtil.getValue(outputValue));
} else
{
result.putPrivate(name, FieldValueUtil.getValue(outputValue));
}
}
return result;
}
static
private Object getPredictedValue(Object object){
return EvaluatorUtil.decode(object);
}
static
private Object getPredictedDisplayValue(Object object, TargetField targetField){
if(object instanceof HasDisplayValue){
HasDisplayValue hasDisplayValue = TypeUtil.cast(HasDisplayValue.class, object);
return hasDisplayValue.getDisplayValue();
}
object = getPredictedValue(object);
Target target = targetField.getTarget();
if(target != null){
TargetValue targetValue = TargetUtil.getTargetValue(target, object);
if(targetValue != null){
String displayValue = targetValue.getDisplayValue();
if(displayValue != null){
return displayValue;
}
}
}
DataField dataField = targetField.getField();
OpType opType = targetField.getOpType();
switch(opType){
case CONTINUOUS:
break;
case CATEGORICAL:
case ORDINAL:
{
Value value = TargetFieldUtil.getValidValue(dataField, object);
if(value != null){
String displayValue = value.getDisplayValue();
if(displayValue != null){
return displayValue;
}
}
}
break;
default:
throw new UnsupportedAttributeException(dataField, opType);
}
// "If the display value is not specified explicitly, then the raw predicted value is used by default"
return object;
}
static
private Double getProbability(Object object, OutputField outputField){
HasProbability hasProbability = TypeUtil.cast(HasProbability.class, object);
Object value = getCategoryValue(object, outputField);
return hasProbability.getProbability(value);
}
static
private Double getConfidence(Object object, OutputField outputField){
HasConfidence hasConfidence = TypeUtil.cast(HasConfidence.class, object);
Object value = getCategoryValue(object, outputField);
return hasConfidence.getConfidence(value);
}
static
private Object getCategoryValue(Object object, OutputField outputField){
Object value = outputField.getValue();
// "If the value attribute is not specified, then the predicted categorical value should be returned as a result"
if(value == null){
return getPredictedValue(object);
}
return value;
}
static
private Number getContinuousResidual(Object value, FieldValue expectedValue){
value = getPredictedValue(value);
return Functions.SUBTRACT.evaluate(expectedValue.asNumber(), (Number)value);
}
static
public Number getDiscreteResidual(Object value, FieldValue expectedValue){
HasProbability hasProbability = TypeUtil.cast(HasProbability.class, value);
value = getPredictedValue(value);
boolean equals = expectedValue.equalsValue(value);
return Functions.SUBTRACT.evaluate(equals ? Numbers.DOUBLE_ONE : Numbers.DOUBLE_ZERO, hasProbability.getProbability(value));
}
static
private String getClusterId(Object object){
HasEntityId hasEntityId = TypeUtil.cast(HasEntityId.class, object);
return hasEntityId.getEntityId();
}
static
private String getEntityId(Object object, OutputField outputField){
HasEntityId hasEntityId = TypeUtil.cast(HasEntityId.class, object);
int rank = outputField.getRank();
if(rank <= 0){
throw new InvalidAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_RANK, rank);
} // End if
if(rank > 1){
HasEntityIdRanking hasEntityIdRanking = TypeUtil.cast(HasEntityIdRanking.class, object);
OutputField.RankOrder rankOrder = outputField.getRankOrder();
switch(rankOrder){
case DESCENDING:
break;
default:
throw new UnsupportedAttributeException(outputField, rankOrder);
}
return getElement(hasEntityIdRanking.getEntityIdRanking(), rank);
}
return hasEntityId.getEntityId();
}
static
public Double getAffinity(Object object, OutputField outputField){
HasAffinity hasAffinity = TypeUtil.cast(HasAffinity.class, object);
int rank = outputField.getRank();
if(rank <= 0){
throw new InvalidAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_RANK, rank);
} // End if
if(rank > 1){
HasAffinityRanking hasAffinityRanking = TypeUtil.cast(HasAffinityRanking.class, object);
OutputField.RankOrder rankOrder = outputField.getRankOrder();
switch(rankOrder){
case DESCENDING:
break;
default:
throw new UnsupportedAttributeException(outputField, rankOrder);
}
return getElement(hasAffinityRanking.getAffinityRanking(), rank);
}
Object value = getCategoryValue(object, outputField);
return hasAffinity.getAffinity(TypeUtil.format(value));
}
static
public Double getEntityAffinity(Object object){
HasEntityAffinity hasEntityAffinity = TypeUtil.cast(HasEntityAffinity.class, object);
return hasEntityAffinity.getEntityAffinity();
}
static
public String getReasonCode(Object object, OutputField outputField){
HasReasonCodeRanking hasReasonCodeRanking = TypeUtil.cast(HasReasonCodeRanking.class, object);
int rank = outputField.getRank();
if(rank <= 0){
throw new InvalidAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_RANK, rank);
}
return getElement(hasReasonCodeRanking.getReasonCodeRanking(), rank);
}
static
public Object getRuleValue(Object object, OutputField outputField){
return getRuleValue(object, outputField, outputField.getRuleFeature());
}
static
public Object getRuleValue(Object object, OutputField outputField, OutputField.RuleFeature ruleFeature){
HasRuleValues hasRuleValues = TypeUtil.cast(HasRuleValues.class, object);
List associationRules = getRuleValues(hasRuleValues, outputField);
String isMultiValued = outputField.getIsMultiValued();
// Return a single result
if(("0").equals(isMultiValued)){
int rank = outputField.getRank();
if(rank <= 0){
throw new InvalidAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_RANK, rank);
}
AssociationRule associationRule = getElement(associationRules, rank);
if(associationRule != null){
return getRuleFeature(hasRuleValues, associationRule, outputField, ruleFeature);
}
return null;
} else
// Return multiple results
if(("1").equals(isMultiValued)){
int size;
int rank = outputField.getRank();
if(rank < 0){
throw new InvalidAttributeException(outputField, PMMLAttributes.OUTPUTFIELD_RANK, rank);
} else
// "A zero value indicates that all output values are to be returned"
if(rank == 0){
size = associationRules.size();
} else
// "A positive value indicates the number of output values to be returned"
{
size = Math.min(rank, associationRules.size());
}
associationRules = associationRules.subList(0, size);
List