private String getNodeId(MissingValueStrategyType missingValueStrategy) throws Exception {
ModelEvaluator<?> evaluator = createModelEvaluator();
TreeModel treeModel = (TreeModel) evaluator.getModel();
treeModel.setMissingValueStrategy(missingValueStrategy);
Map<FieldName, ?> arguments =
createArguments("outlook", "sunny", "temperature", null, "humidity", null);
Map<FieldName, ?> result = evaluator.evaluate(arguments);
return getEntityId(result.get(evaluator.getTargetField()));
}
static Object evaluateRegressionInternal(
FieldName name, Object value, ModelEvaluationContext context) {
ModelEvaluator<?> evaluator = context.getModelEvaluator();
if (Objects.equals(Evaluator.DEFAULT_TARGET, name)) {
DataField dataField = evaluator.getDataField();
if (value != null) {
value = TypeUtil.cast(dataField.getDataType(), value);
}
} else {
Target target = evaluator.getTarget(name);
if (target != null) {
if (value == null) {
value = getDefaultValue(target);
} // End if
if (value != null) {
value = processValue(target, (Double) value);
}
}
DataField dataField = evaluator.getDataField(name);
if (dataField == null) {
throw new MissingFieldException(name);
} // End if
if (value != null) {
value = TypeUtil.cast(dataField.getDataType(), value);
}
MiningField miningField = evaluator.getMiningField(name);
context.declare(
name, FieldValueUtil.createTargetValue(dataField, miningField, target, value));
}
return value;
}
static Classification evaluateClassificationInternal(
FieldName name, Classification value, ModelEvaluationContext context) {
ModelEvaluator<?> evaluator = context.getModelEvaluator();
if (Objects.equals(Evaluator.DEFAULT_TARGET, name)) {
DataField dataField = evaluator.getDataField();
if (value != null) {
value.computeResult(dataField.getDataType());
}
} else {
Target target = evaluator.getTarget(name);
if (target != null) {
if (value == null) {
value = getPriorProbabilities(target);
}
}
DataField dataField = evaluator.getDataField(name);
if (dataField == null) {
throw new MissingFieldException(name);
} // End if
if (value != null) {
value.computeResult(dataField.getDataType());
}
MiningField miningField = evaluator.getMiningField(name);
context.declare(
name,
FieldValueUtil.createTargetValue(
dataField, miningField, target, value != null ? value.getResult() : null));
}
return value;
}
public static Map<FieldName, ? extends Classification> evaluateClassification(
Classification value, ModelEvaluationContext context) {
ModelEvaluator<?> evaluator = context.getModelEvaluator();
return evaluateClassification(evaluator.getTargetField(), value, context);
}
public static Map<FieldName, ?> evaluateRegression(Double value, ModelEvaluationContext context) {
ModelEvaluator<?> evaluator = context.getModelEvaluator();
return evaluateRegression(evaluator.getTargetField(), value, context);
}
/**
* 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.
*/
@SuppressWarnings(value = {"fallthrough"})
public static Map<FieldName, ?> evaluate(
Map<FieldName, ?> predictions, ModelEvaluationContext context) {
ModelEvaluator<?> modelEvaluator = context.getModelEvaluator();
Model model = modelEvaluator.getModel();
Output output = model.getOutput();
if (output == null) {
return predictions;
}
Map<FieldName, Object> result = new LinkedHashMap<>(predictions);
List<OutputField> outputFields = output.getOutputFields();
outputFields:
for (OutputField outputField : outputFields) {
FieldName targetFieldName = outputField.getTargetField();
Object targetValue = null;
ResultFeature resultFeature = outputField.getResultFeature();
String segmentId = outputField.getSegmentId();
SegmentResult segmentPredictions = null;
// Load the target value of the specified segment
if (segmentId != null) {
if (!(model instanceof MiningModel)) {
throw new InvalidFeatureException(outputField);
}
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 (targetFieldName != null) {
if (!segmentPredictions.containsKey(targetFieldName)) {
throw new MissingValueException(targetFieldName, outputField);
}
targetValue = segmentPredictions.get(targetFieldName);
} else {
targetValue = segmentPredictions.getTargetValue();
}
} else
// Load the target value
{
switch (resultFeature) {
case ENTITY_ID:
{
// "Result feature entityId returns the id of the winning segment"
if (model instanceof MiningModel) {
targetValue = TypeUtil.cast(HasEntityId.class, predictions);
break;
}
}
// Falls through
default:
{
if (targetFieldName == null) {
targetFieldName = modelEvaluator.getTargetFieldName();
} // End if
if (!predictions.containsKey(targetFieldName)) {
throw new MissingValueException(targetFieldName, outputField);
}
targetValue = predictions.get(targetFieldName);
}
break;
}
}
// "If the target value is missing, then the result delivered by this OutputField is missing"
if (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:
{
DataField dataField = modelEvaluator.getDataField(targetFieldName);
if (dataField == null) {
throw new MissingFieldException(targetFieldName, outputField);
}
Target target = modelEvaluator.getTarget(targetFieldName);
value = getPredictedDisplayValue(targetValue, dataField, target);
}
break;
case TRANSFORMED_VALUE:
case DECISION:
{
if (segmentId != null) {
String name = outputField.getValue();
if (name == null) {
throw new InvalidFeatureException(outputField);
}
Expression expression = outputField.getExpression();
if (expression != null) {
throw new InvalidFeatureException(outputField);
}
value = segmentPredictions.get(FieldName.create(name));
break;
}
Expression expression = outputField.getExpression();
if (expression == null) {
throw new InvalidFeatureException(outputField);
}
value = FieldValueUtil.getValue(ExpressionUtil.evaluate(expression, context));
}
break;
case PROBABILITY:
{
value = getProbability(targetValue, outputField);
}
break;
case RESIDUAL:
{
FieldValue expectedTargetValue = context.evaluate(targetFieldName);
if (expectedTargetValue == null) {
throw new MissingValueException(targetFieldName, outputField);
}
DataField dataField = modelEvaluator.getDataField(targetFieldName);
OpType opType = dataField.getOpType();
switch (opType) {
case CONTINUOUS:
value = getContinuousResidual(targetValue, expectedTargetValue);
break;
case CATEGORICAL:
value = getCategoricalResidual(targetValue, expectedTargetValue);
break;
default:
throw new UnsupportedFeatureException(dataField, opType);
}
}
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:
{
String 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 CONFIDENCE:
{
value = getRuleValue(targetValue, outputField, OutputField.RuleFeature.CONFIDENCE);
}
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 WARNING:
{
value = context.getWarnings();
}
break;
default:
throw new UnsupportedFeatureException(outputField, resultFeature);
}
FieldValue outputValue = FieldValueUtil.create(outputField, value);
// The result of one output field becomes available to other output fields
context.declare(outputField.getName(), outputValue);
result.put(outputField.getName(), FieldValueUtil.getValue(outputValue));
}
return result;
}
/** @throws TypeAnalysisException If the data type cannot be determined. */
public static DataType getDataType(OutputField outputField, ModelEvaluator<?> modelEvaluator) {
FieldName name = outputField.getName();
DataType dataType = outputField.getDataType();
if (dataType != null) {
return dataType;
}
String segmentId = outputField.getSegmentId();
if (segmentId != null) {
throw new TypeAnalysisException(outputField);
}
ResultFeature resultFeature = outputField.getResultFeature();
switch (resultFeature) {
case PREDICTED_VALUE:
case TRANSFORMED_VALUE:
case DECISION:
{
OutputField evaluatorOutputField = modelEvaluator.getOutputField(name);
if (!(outputField).equals(evaluatorOutputField)) {
throw new TypeAnalysisException(outputField);
}
}
break;
default:
break;
} // End switch
switch (resultFeature) {
case PREDICTED_VALUE:
{
FieldName targetFieldName = outputField.getTargetField();
if (targetFieldName == null) {
targetFieldName = modelEvaluator.getTargetFieldName();
}
DataField dataField = modelEvaluator.getDataField(targetFieldName);
if (dataField == null) {
throw new MissingFieldException(targetFieldName, outputField);
}
return dataField.getDataType();
}
case PREDICTED_DISPLAY_VALUE:
{
return DataType.STRING; // XXX
}
case TRANSFORMED_VALUE:
case DECISION:
{
Expression expression = outputField.getExpression();
if (expression == null) {
throw new InvalidFeatureException(outputField);
}
return ExpressionUtil.getDataType(expression, modelEvaluator);
}
case PROBABILITY:
case RESIDUAL:
case STANDARD_ERROR:
{
return DataType.DOUBLE;
}
case ENTITY_ID:
case CLUSTER_ID:
{
return DataType.STRING;
}
case AFFINITY:
case ENTITY_AFFINITY:
case CLUSTER_AFFINITY:
{
return DataType.DOUBLE;
}
case REASON_CODE:
{
return DataType.STRING;
}
case RULE_VALUE:
{
return getRuleDataType(outputField);
}
case ANTECEDENT:
{
return getRuleDataType(outputField, OutputField.RuleFeature.ANTECEDENT);
}
case CONSEQUENT:
{
return getRuleDataType(outputField, OutputField.RuleFeature.CONSEQUENT);
}
case RULE:
{
return getRuleDataType(outputField, OutputField.RuleFeature.RULE);
}
case RULE_ID:
{
return getRuleDataType(outputField, OutputField.RuleFeature.RULE_ID);
}
case SUPPORT:
{
return getRuleDataType(outputField, OutputField.RuleFeature.SUPPORT);
}
case CONFIDENCE:
{
return getRuleDataType(outputField, OutputField.RuleFeature.CONFIDENCE);
}
case LIFT:
{
return getRuleDataType(outputField, OutputField.RuleFeature.LIFT);
}
case LEVERAGE:
{
return getRuleDataType(outputField, OutputField.RuleFeature.LEVERAGE);
}
case WARNING:
{
throw new TypeAnalysisException(outputField);
}
default:
throw new UnsupportedFeatureException(outputField, resultFeature);
}
}
