Uses of Class
org.jpmml.converter.Schema

Packages that use Schema

Package	Description
org.jpmml.converter
org.jpmml.converter.mining
org.jpmml.converter.regression
org.jpmml.converter.support_vector_machine

Uses of Schema in org.jpmml.converter

Methods in org.jpmml.converter that return Schema

Modifier and Type	Method and Description
Schema	Schema.toAnonymousRegressorSchema(org.dmg.pmml.DataType dataType)
Schema	Schema.toAnonymousSchema()
Schema	Schema.toEmptySchema()
Schema	Schema.toRelabeledSchema(Label label)
Schema	Schema.toSubSchema(int[] indexes)
Schema	Schema.toTransformedSchema(Function<Feature,Feature> function)

Uses of Schema in org.jpmml.converter.mining

Methods in org.jpmml.converter.mining with parameters of type Schema

Modifier and Type	Method and Description
static org.dmg.pmml.mining.MiningModel	MiningModelUtil.createBinaryLogisticClassification(org.dmg.pmml.Model model, double coefficient, double intercept, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.mining.MiningModel	MiningModelUtil.createClassification(List<? extends org.dmg.pmml.Model> models, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.mining.MiningModel	MiningModelUtil.createRegression(org.dmg.pmml.Model model, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Schema schema)

Uses of Schema in org.jpmml.converter.regression

Methods in org.jpmml.converter.regression with parameters of type Schema

Modifier and Type	Method and Description
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createBinaryLogisticClassification(List<? extends Feature> features, List<? extends Number> coefficients, Number intercept, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createBinaryLogisticClassification(org.dmg.pmml.MathContext mathContext, List<? extends Feature> features, List<? extends Number> coefficients, Number intercept, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createOrdinalClassification(Feature feature, List<? extends Number> thresholds, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createOrdinalClassification(org.dmg.pmml.MathContext mathContext, Feature feature, List<? extends Number> thresholds, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, boolean hasProbabilityDistribution, Schema schema)
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createRegression(List<? extends Feature> features, List<? extends Number> coefficients, Number intercept, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Schema schema)
static org.dmg.pmml.regression.RegressionModel	RegressionModelUtil.createRegression(org.dmg.pmml.MathContext mathContext, List<? extends Feature> features, List<? extends Number> coefficients, Number intercept, org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Schema schema)

Uses of Schema in org.jpmml.converter.support_vector_machine

Methods in org.jpmml.converter.support_vector_machine with parameters of type Schema

Modifier and Type	Method and Description
static org.dmg.pmml.support_vector_machine.SupportVectorMachineModel	LibSVMUtil.createClassification(org.dmg.pmml.support_vector_machine.Kernel kernel, Matrix<? extends Number> sv, List<Integer> nSv, List<String> ids, List<? extends Number> rho, List<? extends Number> coefs, Schema schema)
static org.dmg.pmml.support_vector_machine.SupportVectorMachineModel	LibSVMUtil.createRegression(org.dmg.pmml.support_vector_machine.Kernel kernel, Matrix<? extends Number> sv, List<String> ids, Number rho, List<? extends Number> coefs, Schema schema)
static org.dmg.pmml.support_vector_machine.VectorDictionary	LibSVMUtil.createVectorDictionary(Matrix<? extends Number> sv, List<String> ids, Schema schema)