oracle.dmt.odm.settings.function
Class RegressionFunctionSettings

java.lang.Object
  |
  +--oracle.dmt.odm.MiningObject
        |
        +--oracle.dmt.odm.LocatableObject
              |
              +--oracle.dmt.odm.settings.function.MiningFunctionSettings
                    |
                    +--oracle.dmt.odm.settings.function.SupervisedFunctionSettings
                          |
                          +--oracle.dmt.odm.settings.function.RegressionFunctionSettings

All Implemented Interfaces:

java.io.Serializable

public class RegressionFunctionSettings

extends SupervisedFunctionSettings

An instance of RegressionFunctionSettings describes the settings necessary to build a Regression (regression) model by using a Support Vector Machine mining algorithm. RegressionFunctionSettings inherits from SupervisedFunctionSettings. It contains an error metric. The specified value of an error is described by an enum to indicate that the metric is used by test to report the model prediction error rate.

Since:

10.0.0

See Also:

Serialized Form

Constructor Summary

RegressionFunctionSettings(LogicalDataSpecification lds, DataUsageSpecification dus)
Creates an instance of RegressionFunctionSettings object.

RegressionFunctionSettings(LogicalDataSpecification lds, DataUsageSpecification dus, MiningAlgorithmSettings algorithm)
Creates an instance of RegressionFunctionSettings object.

Method Summary

static RegressionFunctionSettings	create(Connection dmsConn, MiningAlgorithmSettings algorithm, PhysicalDataSpecification pdsDataSpec, java.lang.String sTargetAttrName, DataPreparationStatus dpStatus) Creates an instance of RegressionFunctionSettings from the specified parameters.
ErrorMetric	getErrorMetric() Returns the value of errorMetric.
MiningAttribute	getTargetAttribute() Returns the target attribute set in this functional settings.
void	setErrorMetric(ErrorMetric errorMetric) Sets the error metric of the input data.
void	validate() Validates the contents of this mining function settings.

Methods inherited from class oracle.dmt.odm.settings.function.SupervisedFunctionSettings

getDesiredAccuracy, getPredictorAttributes, getTargetAttributes, getUnpreparedPredictorAttributes, setDesiredAccuracy

Methods inherited from class oracle.dmt.odm.settings.function.MiningFunctionSettings

activateAll, adjustAttributesType, adjustAttributeUsage, adjustAttributeUsage, adjustDataPreparationStatus, adjustSparsitySpecification, getDataUsageSpecification, getLogicalDataSpecification, getMiningAlgorithmName, getMiningAlgorithmSettings, getMiningAttributes, getMiningFunction, getName, getSettingsID, getSupplementalAttributes, getValidateBeforeStore, listContents, listContents, listContents, listContents, remove, rename, restore, restore, restorePastVersion, restorePastVersion, setDataUsageSpecification, setLogicalDataSpecification, setMiningAlgorithmName, setMiningAlgorithmSettings, setMiningFunction, setValidateBeforeStore, store

Methods inherited from class java.lang.Object

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

Constructor Detail

RegressionFunctionSettings

public RegressionFunctionSettings(LogicalDataSpecification lds,
DataUsageSpecification dus,
MiningAlgorithmSettings algorithm)
                           throws InvalidArgumentException

Creates an instance of RegressionFunctionSettings object.

Parameters:

lds - An instance of LogicalDataSpecification that specifies the logical representation of the input data used for model building

dus - An instance of DataUsageSpecification that defines how the logical data is to be used for model building

algorithm - An instance of MiningAlgorithmSettings that specifies a classification algorithm to be used for model building. If null, a default algorithm is chosen by the DMS.

Throws:

InvalidArgumentException -

• if lds is null, or
• if dus is null.

RegressionFunctionSettings

public RegressionFunctionSettings(LogicalDataSpecification lds,
DataUsageSpecification dus)
                           throws InvalidArgumentException

Creates an instance of RegressionFunctionSettings object. A default algorithm settings is selected by the DMS, and applied to model building.

Parameters:

lds - An instance of LogicalDataSpecification that specifies the logical representation of the input data used for model building

dus - An instance of DataUsageSpecification that defines how the logical data is to be used for model building

Throws:

InvalidArgumentException -

• if lds is null, or
• if dus is null.

Method Detail

validate

public void validate()
              throws MiningObjectException

Validates the contents of this mining function settings.

Throws:

MiningObjectException - when this mining function settings is invalid

create

public static RegressionFunctionSettings create(Connection dmsConn,
MiningAlgorithmSettings algorithm,
PhysicalDataSpecification pdsDataSpec,
                                                java.lang.String sTargetAttrName,
DataPreparationStatus dpStatus)
                                                                          throws java.sql.SQLException,
InvalidArgumentException,
MiningObjectException,
ODMException

Creates an instance of RegressionFunctionSettings from the specified parameters.

Parameters:

dmsConn - A connection to the data mining server

algorithm - An instance of MiningAlgorithmSettings

pdsDataSpec - An instance of PhysicalDataSpecification that specifies the input data

sTargetAttrName - The name of the target attribute

dpStatus - An instance of DataPreparationStatus that indicates whether the data is discretized.

Returns:

RegressionFunctionSettings - A created instance of Regression function settings

Throws:

InvalidArgumentException - thrown when

• if dmsConn is null,
• if pdsDataSpec is null,
• if sTargetAttrName is null,
• if atTargetAttributeType is neither string nor integer.

java.sql.SQLException - when an error occurs during access to the input data.

MiningObjectException - inherited exception.

ODMException

setErrorMetric

public void setErrorMetric(ErrorMetric errorMetric)
                    throws InvalidArgumentException

Sets the error metric of the input data.

Throws:

InvalidArgumentException - when errorMetric is null.

See Also:

ErrorMetric

getErrorMetric

public ErrorMetric getErrorMetric()

Returns the value of errorMetric.

Returns:

the value of the error metric

getTargetAttribute

public MiningAttribute getTargetAttribute()
                                                       throws MiningObjectException

Returns the target attribute set in this functional settings.

Returns:

The target mining attribute

Throws:

MiningObjectException - when the target attributes are nissing.

See Also:

AttributeUsage