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oracle.dmt.jdm.supervised.regression
Class OraRegressionApplySettings
java.lang.Object
oracle.dmt.jdm.OraDMObject
oracle.dmt.jdm.OraMiningObject
oracle.dmt.jdm.task.apply.OraApplySettings
oracle.dmt.jdm.supervised.regression.OraRegressionApplySettings
- All Implemented Interfaces:
- javax.datamining.task.apply.ApplySettings, javax.datamining.MiningObject, oracle.dmt.jdm.OraPLSQLConstants, javax.datamining.supervised.regression.RegressionApplySettings
- public class OraRegressionApplySettings
- extends oracle.dmt.jdm.task.apply.OraApplySettings
- implements javax.datamining.supervised.regression.RegressionApplySettings
OraRegressionApplySettings
provides set and get methods to specify the target attribute normalization details. If user specifies target attribute normalization details, it will be used to denormalize the prediction values in the apply operation.
Fields inherited from class oracle.dmt.jdm.task.apply.OraApplySettings |
ALL_PREDICTIONS_APPLY_OUTPUT, DEFAULT_APPLY_OUTPUT, MULTIPLE_ROW_ALL, MULTIPLE_ROW_DEFAULT, MULTIPLE_ROW_RANKED, SINGLE_ROW_AS_SPECIFIED, TARGET_OR_CLUID_APPLY_OUTPUT, TOP_PREDICTION_APPLY_OUTPUT |
Methods inherited from class oracle.dmt.jdm.task.apply.OraApplySettings |
getAttributeNames, getContentAttrValue, getFunction, getMappedContentsEnums, getObjectType, getSourceDestinationMap, isInputObject, resetMapping, setSourceDestinationMap, verify |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface javax.datamining.task.apply.ApplySettings |
getSourceDestinationMap, resetMapping, setSourceDestinationMap, verify |
Methods inherited from interface javax.datamining.MiningObject |
getCreationDate, getCreatorInfo, getDescription, getName, getObjectIdentifier, getObjectType, setDescription |
setTargetNormalizationDetails
public void setTargetNormalizationDetails(java.lang.Double shiftValue,
java.lang.Double scaleValue)
- Sets the normalization details of the target columns. By default these values will be null. If the target column is normalized, then the predictions done by the apply operation will be normalized values. To automate the denormalization of the target values as part of the apply operation use this method. operation will be normalized.
-
- Parameters:
shiftValue
-
scaleValue
-
getTargetNormalizationShiftValue
public java.lang.Double getTargetNormalizationShiftValue()
- Returns the specified normalization shift value of the target column. It returns null value if it is not specified.
-
- Returns:
getTargetNormalizationScaleValue
public java.lang.Double getTargetNormalizationScaleValue()
- Returns the specified normalization scale value of the target column. It returns null value if it is not specified.
-
- Returns:
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