| Package | Description |
|---|---|
| org.openimaj.hadoop.tools.fastkmeans | |
| org.openimaj.ml.clustering.kmeans |
K-Means in OpenIMAJ is designed to be both extremely fast and flexible.
|
| org.openimaj.ml.clustering.random |
| Modifier and Type | Method and Description |
|---|---|
static ByteCentroidsResult |
AKMeans.completeCentroids(String centroids,
String selected,
HadoopFastKMeansOptions options)
Given the location of a binary dump of centroids on the HDFS, load the
binary dump and construct a proper
ByteKMeans instance |
static ByteCentroidsResult |
AKMeans.sequenceFileToCluster(String initialCentroids,
int k)
load some initially selected centroids from
FeatureSelect as a
ByteKMeans instance |
| Modifier and Type | Class and Description |
|---|---|
static class |
ByteKMeans.Result
Result object for ByteKMeans, extending ByteCentroidsResult and ByteNearestNeighboursProvider,
as well as giving access to state information from the operation of the K-Means algorithm
(i.e.
|
| Modifier and Type | Field and Description |
|---|---|
ByteCentroidsResult |
HierarchicalByteKMeansResult.Node.result
ByteCentroidsResult for this node |
| Modifier and Type | Method and Description |
|---|---|
ByteCentroidsResult |
RandomSetByteClusterer.cluster(byte[][] data)
Selects K elements from the provided data as the centroids of the clusters.
|
ByteCentroidsResult |
RandomByteClusterer.cluster(byte[][] data)
Selects K elements from the provided data as the centroids of the clusters.
|
ByteCentroidsResult |
RandomSetByteClusterer.cluster(DataSource<byte[]> data)
Selects K elements from the provided
DataSource as the centroids of the clusters. |
ByteCentroidsResult |
RandomByteClusterer.cluster(DataSource<byte[]> data)
Selects K elements from the provided
DataSource as the centroids of the clusters. |