@Bindable(prefix="BisectingKMeansClusteringAlgorithm",
inherit=CommonAttributes.class)
public class BisectingKMeansClusteringAlgorithm
extends ProcessingComponentBase
implements IClusteringAlgorithm
| Modifier and Type | Field and Description |
|---|---|
int |
clusterCount
The number of clusters to create.
|
List<Cluster> |
clusters |
List<Document> |
documents |
int |
labelCount
Label count.
|
LabelFormatter |
labelFormatter
Cluster label formatter, contains bindable attributes.
|
TermDocumentMatrixBuilder |
matrixBuilder
Term-document matrix builder for the algorithm, contains bindable attributes.
|
TermDocumentMatrixReducer |
matrixReducer
Term-document matrix reducer for the algorithm, contains bindable attributes.
|
int |
maxIterations
The maximum number of k-means iterations to perform.
|
int |
partitionCount
Partition count.
|
BasicPreprocessingPipeline |
preprocessingPipeline
Common preprocessing tasks handler, contains bindable attributes.
|
boolean |
useDimensionalityReduction
Use dimensionality reduction.
|
| Constructor and Description |
|---|
BisectingKMeansClusteringAlgorithm() |
| Modifier and Type | Method and Description |
|---|---|
void |
process()
Performs the processing required to fulfill the request.
|
afterProcessing, beforeProcessing, dispose, getContext, getSharedExecutor, initclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitafterProcessing, beforeProcessing, dispose, init@Processing @Input @Required @Internal @Attribute(key="documents", inherit=true) public List<Document> documents
@Processing @Output @Internal @Attribute(key="clusters", inherit=true) public List<Cluster> clusters
@Processing @Input @Attribute @IntRange(min=2) @Group(value="Clusters") @Level(value=BASIC) @Label(value="Cluster count") public int clusterCount
@Processing @Input @Attribute @IntRange(min=1) @Group(value="K-means") @Level(value=BASIC) @Label(value="Maximum iterations") public int maxIterations
@Processing @Input @Attribute @Group(value="K-means") @Level(value=BASIC) @Label(value="Use dimensionality reduction") public boolean useDimensionalityReduction
true, k-means will be applied on the
dimensionality-reduced term-document matrix with the number of dimensions being
equal to the number of requested clusters. If false, the k-means will
be performed directly on the original term-document matrix.@Processing @Input @Attribute @IntRange(min=2, max=10) @Group(value="K-means") @Level(value=BASIC) @Label(value="Partition count") public int partitionCount
@Processing @Input @Attribute @IntRange(min=1, max=10) @Group(value="Clusters") @Level(value=BASIC) @Label(value="Label count") public int labelCount
public final BasicPreprocessingPipeline preprocessingPipeline
public final TermDocumentMatrixBuilder matrixBuilder
public final TermDocumentMatrixReducer matrixReducer
public final LabelFormatter labelFormatter
public void process()
throws ProcessingException
IProcessingComponentprocess in interface IProcessingComponentprocess in class ProcessingComponentBaseProcessingException - when processing failed. If thrown, the
IProcessingComponent.afterProcessing() method will be called and the component will
be ready to accept further requests or to be disposed of. Finally, the
exception will be rethrown from the controller method that caused the
component to perform processing.