MOA 12.03
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moa.clusterers.WekaClusteringAlgorithm Class Reference
Inheritance diagram for moa.clusterers.WekaClusteringAlgorithm:
Collaboration diagram for moa.clusterers.WekaClusteringAlgorithm:

List of all members.

Public Member Functions

 WekaClusteringAlgorithm ()
void resetLearningImpl ()
void trainOnInstanceImpl (Instance inst)
Clustering getClusteringResult ()
Instances getDataset (int numdim, int numclass)
void getModelDescription (StringBuilder out, int indent)
boolean isRandomizable ()
double[] getVotesForInstance (Instance inst)
boolean keepClassLabel ()
String getPurposeString ()
 Gets the purpose of this object.

Public Attributes

IntOption horizonOption
MultiChoiceOption wekaAlgorithmOption
StringOption parameterOption

Protected Member Functions

Measurement[] getModelMeasurementsImpl ()

Detailed Description

Definition at line 40 of file WekaClusteringAlgorithm.java.


Constructor & Destructor Documentation

moa.clusterers.WekaClusteringAlgorithm.WekaClusteringAlgorithm ( )

Definition at line 57 of file WekaClusteringAlgorithm.java.


Member Function Documentation

Clustering moa.clusterers.WekaClusteringAlgorithm.getClusteringResult ( )

Implements moa.clusterers.Clusterer.

Definition at line 127 of file WekaClusteringAlgorithm.java.

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Instances moa.clusterers.WekaClusteringAlgorithm.getDataset ( int  numdim,
int  numclass 
)
void moa.clusterers.WekaClusteringAlgorithm.getModelDescription ( StringBuilder  out,
int  indent 
) [virtual]

Implements moa.clusterers.AbstractClusterer.

Definition at line 196 of file WekaClusteringAlgorithm.java.

Measurement [] moa.clusterers.WekaClusteringAlgorithm.getModelMeasurementsImpl ( ) [protected, virtual]

Implements moa.clusterers.AbstractClusterer.

Definition at line 191 of file WekaClusteringAlgorithm.java.

String moa.clusterers.WekaClusteringAlgorithm.getPurposeString ( )

Gets the purpose of this object.

Returns:
the string with the purpose of this object

Reimplemented from moa.clusterers.AbstractClusterer.

Definition at line 213 of file WekaClusteringAlgorithm.java.

double [] moa.clusterers.WekaClusteringAlgorithm.getVotesForInstance ( Instance  inst)

Implements moa.clusterers.Clusterer.

Definition at line 203 of file WekaClusteringAlgorithm.java.

boolean moa.clusterers.WekaClusteringAlgorithm.isRandomizable ( )

Implements moa.clusterers.Clusterer.

Definition at line 199 of file WekaClusteringAlgorithm.java.

boolean moa.clusterers.WekaClusteringAlgorithm.keepClassLabel ( )

Reimplemented from moa.clusterers.AbstractClusterer.

Definition at line 208 of file WekaClusteringAlgorithm.java.

void moa.clusterers.WekaClusteringAlgorithm.resetLearningImpl ( ) [virtual]

Implements moa.clusterers.AbstractClusterer.

Definition at line 102 of file WekaClusteringAlgorithm.java.

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void moa.clusterers.WekaClusteringAlgorithm.trainOnInstanceImpl ( Instance  inst) [virtual]

Implements moa.clusterers.AbstractClusterer.

Definition at line 120 of file WekaClusteringAlgorithm.java.

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Member Data Documentation

Initial value:
 new IntOption("horizon",
                        'h', "Range of the window.", 1000)

Definition at line 44 of file WekaClusteringAlgorithm.java.

Referenced by moa.clusterers.WekaClusteringAlgorithm.WekaClusteringAlgorithm().

Initial value:
 new StringOption("parameter", 'p', 
                        "Parameters that will be passed to the weka algorithm. (e.g. '-N 5' for using SimpleKmeans with 5 clusters)", "-N 5 -S 8")

Definition at line 49 of file WekaClusteringAlgorithm.java.

Referenced by moa.clusterers.WekaClusteringAlgorithm.resetLearningImpl(), and moa.clusterers.WekaClusteringAlgorithm.WekaClusteringAlgorithm().


The documentation for this class was generated from the following file:
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