| Package | Description |
|---|---|
| org.jpmml.evaluator | |
| org.jpmml.evaluator.mining | |
| org.jpmml.evaluator.regression | |
| org.jpmml.evaluator.scorecard |
| Modifier and Type | Method and Description |
|---|---|
ValueMap<Object,V> |
ProbabilityAggregator.averageMap() |
ValueMap<K,V> |
Classification.getValues() |
ValueMap<Object,V> |
ProbabilityAggregator.maxMap(Collection<?> categories) |
ValueMap<Object,V> |
ProbabilityAggregator.medianMap(Collection<?> categories) |
ValueMap<K,V> |
VoteAggregator.sumMap() |
ValueMap<Object,V> |
ProbabilityAggregator.weightedAverageMap() |
| Modifier and Type | Method and Description |
|---|---|
protected <V extends Number> |
ModelEvaluator.createClassification(ValueMap<Object,V> values) |
| Constructor and Description |
|---|
AffinityDistribution(Classification.Type type,
ValueMap<String,V> values,
Object result) |
Classification(Classification.Type type,
ValueMap<K,V> values) |
ConfidenceDistribution(ValueMap<Object,V> confidences) |
EntityClassification(Classification.Type type,
ValueMap<K,V> values) |
ProbabilityDistribution(ValueMap<Object,V> probabilities) |
VoteDistribution(ValueMap<Object,V> votes) |
| Modifier and Type | Method and Description |
|---|---|
static <V extends Number> |
MiningModelUtil.aggregateProbabilities(ValueFactory<V> valueFactory,
org.dmg.pmml.mining.Segmentation.MultipleModelMethod multipleModelMethod,
org.dmg.pmml.mining.Segmentation.MissingPredictionTreatment missingPredictionTreatment,
Number missingThreshold,
List<?> categories,
List<SegmentResult> segmentResults) |
static <V extends Number> |
MiningModelUtil.aggregateVotes(ValueFactory<V> valueFactory,
org.dmg.pmml.mining.Segmentation.MultipleModelMethod multipleModelMethod,
org.dmg.pmml.mining.Segmentation.MissingPredictionTreatment missingPredictionTreatment,
Number missingThreshold,
List<SegmentResult> segmentResults) |
| Modifier and Type | Method and Description |
|---|---|
static <K,V extends Number> |
RegressionModelUtil.computeBinomialProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
static <K,V extends Number> |
RegressionModelUtil.computeMultinomialProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
static <K,V extends Number> |
RegressionModelUtil.computeOrdinalProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
| Modifier and Type | Method and Description |
|---|---|
static <K,V extends Number> |
RegressionModelUtil.computeBinomialProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
static <K,V extends Number> |
RegressionModelUtil.computeMultinomialProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
static <K,V extends Number> |
RegressionModelUtil.computeOrdinalProbabilities(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod,
ValueMap<K,V> values) |
| Modifier and Type | Method and Description |
|---|---|
ValueMap<String,V> |
ComplexScorecardScore.getReasonCodePoints() |
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