org.knime.base.node.mine.decisiontree2
Enum PMMLMissingValueStrategy

java.lang.Object
  extended by java.lang.Enum<PMMLMissingValueStrategy>
      extended by org.knime.base.node.mine.decisiontree2.PMMLMissingValueStrategy
All Implemented Interfaces:
Serializable, Comparable<PMMLMissingValueStrategy>

public enum PMMLMissingValueStrategy
extends Enum<PMMLMissingValueStrategy>

Represents the missing value strategies as defined in PMML (http://www.dmg.org/v4-0/TreeModel.html#MissValStrategies).

Author:
Dominik Morent, KNIME.com, Zurich, Switzerland

Enum Constant Summary
AGGREGATE_NODES
          aggregateNodes strategy as specified in PMML.
DEFAULT_CHILD
          defaultChild strategy as specified in PMML.
LAST_PREDICTION
          lastPrediction strategy as specified in PMML.
NONE
          none strategy as specified in PMML.
NULL_PREDICTION
          nullPrediction strategy as specified in PMML.
WEIGHTED_CONFIDENCE
          weightedConfidence strategy as specified in PMML.
 
Method Summary
static PMMLMissingValueStrategy get(String represent)
          Returns the corresponding missing value strategy to the string representation.
static PMMLMissingValueStrategy getDefault()
          Returns the default missing value strategy.
 String toString()
          
static PMMLMissingValueStrategy valueOf(String name)
          Returns the enum constant of this type with the specified name.
static PMMLMissingValueStrategy[] values()
          Returns an array containing the constants of this enum type, in the order they are declared.
 
Methods inherited from class java.lang.Enum
clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, valueOf
 
Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait
 

Enum Constant Detail

LAST_PREDICTION

public static final PMMLMissingValueStrategy LAST_PREDICTION
lastPrediction strategy as specified in PMML.


NULL_PREDICTION

public static final PMMLMissingValueStrategy NULL_PREDICTION
nullPrediction strategy as specified in PMML. not yet supported


DEFAULT_CHILD

public static final PMMLMissingValueStrategy DEFAULT_CHILD
defaultChild strategy as specified in PMML.


WEIGHTED_CONFIDENCE

public static final PMMLMissingValueStrategy WEIGHTED_CONFIDENCE
weightedConfidence strategy as specified in PMML. not yet supported


AGGREGATE_NODES

public static final PMMLMissingValueStrategy AGGREGATE_NODES
aggregateNodes strategy as specified in PMML. not yet supported


NONE

public static final PMMLMissingValueStrategy NONE
none strategy as specified in PMML.

Method Detail

values

public static PMMLMissingValueStrategy[] values()
Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:
for (PMMLMissingValueStrategy c : PMMLMissingValueStrategy.values())
    System.out.println(c);

Returns:
an array containing the constants of this enum type, in the order they are declared

valueOf

public static PMMLMissingValueStrategy valueOf(String name)
Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:
name - the name of the enum constant to be returned.
Returns:
the enum constant with the specified name
Throws:
IllegalArgumentException - if this enum type has no constant with the specified name
NullPointerException - if the argument is null

toString

public String toString()

Overrides:
toString in class Enum<PMMLMissingValueStrategy>

get

public static PMMLMissingValueStrategy get(String represent)
Returns the corresponding missing value strategy to the string representation.

Parameters:
represent - the representation to retrieve the strategy for
Returns:
the missing value strategy

getDefault

public static PMMLMissingValueStrategy getDefault()
Returns the default missing value strategy.

Returns:
the default strategy


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University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
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