Package | Description |
---|---|
org.openimaj.knn | |
org.openimaj.knn.approximate | |
org.openimaj.ml.clustering.dbscan | |
org.openimaj.ml.clustering.kmeans |
K-Means in OpenIMAJ is designed to be both extremely fast and flexible.
|
Modifier and Type | Class and Description |
---|---|
static class |
ByteNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
ByteNearestNeighboursExact s. |
static class |
DoubleNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
DoubleNearestNeighboursExact s. |
static class |
FloatNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
FloatNearestNeighboursExact s. |
static class |
IntNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
IntNearestNeighboursExact s. |
static class |
LongNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
LongNearestNeighboursExact s. |
static class |
ObjectNearestNeighboursExact.Factory<T>
NearestNeighboursFactory for producing
ObjectNearestNeighboursExact s. |
static class |
ShortNearestNeighboursExact.Factory
NearestNeighboursFactory for producing
ShortNearestNeighboursExact s. |
Modifier and Type | Class and Description |
---|---|
static class |
ByteNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
ByteNearestNeighboursKDTree s. |
static class |
DoubleNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
DoubleNearestNeighboursKDTree s. |
static class |
FloatNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
FloatNearestNeighboursKDTree s. |
static class |
IntNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
IntNearestNeighboursKDTree s. |
static class |
LongNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
LongNearestNeighboursKDTree s. |
static class |
ShortNearestNeighboursKDTree.Factory
NearestNeighboursFactory for producing
ShortNearestNeighboursKDTree s. |
Constructor and Description |
---|
DoubleNNDBSCAN(double eps,
int minPts,
NearestNeighboursFactory<? extends DoubleNearestNeighbours,double[]> nnf)
Perform a DBScane with this configuration
|
Modifier and Type | Field and Description |
---|---|
protected NearestNeighboursFactory<? extends NN,DATA> |
KMeansConfiguration.factory
The factory for producing the
NearestNeighbours objects used in
assignment. |
Modifier and Type | Method and Description |
---|---|
NearestNeighboursFactory<? extends NN,DATA> |
KMeansConfiguration.getNearestNeighbourFactory()
Get the factory that produces the
NearestNeighbours during
clustering. |
Modifier and Type | Method and Description |
---|---|
void |
KMeansConfiguration.setNearestNeighbourFactory(NearestNeighboursFactory<? extends NN,DATA> factory)
Set the factory that produces the
NearestNeighbours during
clustering. |
Constructor and Description |
---|
KMeansConfiguration(int K,
NearestNeighboursFactory<? extends NN,DATA> nnFactory)
Create configuration for data that will create
K clusters. |
KMeansConfiguration(int K,
NearestNeighboursFactory<? extends NN,DATA> nnFactory,
int niters)
Create configuration for data that will create
K clusters. |
KMeansConfiguration(int K,
NearestNeighboursFactory<? extends NN,DATA> nnFactory,
int niters,
ExecutorService threadpool)
Create configuration for data that will create
K clusters. |
KMeansConfiguration(int K,
NearestNeighboursFactory<? extends NN,DATA> nnFactory,
int niters,
int blockSize,
ExecutorService threadpool)
Create configuration for data with
M dimensions that will
create K clusters. |