public class DoubleKDTreeClusterer extends Object implements SpatialClusterer<KDTreeClusters,double[]>
| Constructor and Description |
|---|
DoubleKDTreeClusterer()
calls:
DoubleKDTreeClusterer() with 0.01 |
DoubleKDTreeClusterer(double varprop) |
DoubleKDTreeClusterer(double varprop,
int startindex,
int ndims) |
DoubleKDTreeClusterer(SplitDetectionMode detectionMode,
double varprop,
int startindex,
int ndims) |
| Modifier and Type | Method and Description |
|---|---|
KDTreeClusters |
cluster(DataSource<double[]> data)
Perform clustering with data from a data source.
|
KDTreeClusters |
cluster(double[][] data)
Perform clustering on the given data.
|
int[][] |
performClustering(double[][] data) |
public DoubleKDTreeClusterer()
DoubleKDTreeClusterer() with 0.01public DoubleKDTreeClusterer(double varprop, int startindex, int ndims)
varprop - the proportion of variance change from the root variance before splitting stopsstartindex - the index to start fromndims - the number of dimensions to split onpublic DoubleKDTreeClusterer(SplitDetectionMode detectionMode, double varprop, int startindex, int ndims)
detectionMode - The SplitDetectionMode given the feature of highest variancevarprop - The minimum proportional variance (compared to the first variance)startindex - the feature start indexndims - the number of features to usepublic DoubleKDTreeClusterer(double varprop)
varprop - the proportion of variance change from the root variance before splitting stopspublic int[][] performClustering(double[][] data)
performClustering in interface Clusterer<double[][]>public KDTreeClusters cluster(double[][] data)
SpatialClusterercluster in interface SpatialClusterer<KDTreeClusters,double[]>data - the data.public KDTreeClusters cluster(DataSource<double[]> data)
SpatialClustererDataSource
could potentially be backed by disk rather in memory.cluster in interface SpatialClusterer<KDTreeClusters,double[]>data - the data.