Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering.em |
Expectation-Maximization clustering algorithm.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.database.datastore |
General data store layer API (along the lines of
Map<DBID, T> - use everywhere!) |
de.lmu.ifi.dbs.elki.database.datastore.memory |
Memory data store implementation for ELKI.
|
de.lmu.ifi.dbs.elki.index.preprocessed |
Index structure based on preprocessors
|
de.lmu.ifi.dbs.elki.index.preprocessed.knn |
Indexes providing KNN and rKNN data.
|
de.lmu.ifi.dbs.elki.parallel.processor |
Processor API of ELKI, and some essential shared processors.
|
Modifier and Type | Method and Description |
---|---|
WritableDataStore<KNNList> |
KNNJoin.run(Relation<V> relation)
Joins in the given spatial database to each object its k-nearest neighbors.
|
Modifier and Type | Method and Description |
---|---|
static double |
EM.assignProbabilitiesToInstances(Relation<? extends NumberVector> relation,
List<? extends EMClusterModel<?>> models,
WritableDataStore<double[]> probClusterIGivenX)
Assigns the current probability values to the instances in the database and
compute the expectation value of the current mixture of distributions.
|
static void |
EM.recomputeCovarianceMatrices(Relation<? extends NumberVector> relation,
WritableDataStore<double[]> probClusterIGivenX,
List<? extends EMClusterModel<?>> models)
Recompute the covariance matrixes.
|
Modifier and Type | Method and Description |
---|---|
private int |
KMeansElkan.assignToNearestCluster(Relation<V> relation,
List<Vector> means,
List<Vector> sums,
List<ModifiableDBIDs> clusters,
WritableIntegerDataStore assignment,
double[] sep,
double[][] cdist,
WritableDoubleDataStore upper,
WritableDataStore<double[]> lower)
Reassign objects, but only if their bounds indicate it is necessary to do
so.
|
private int |
KMeansElkan.initialAssignToNearestCluster(Relation<V> relation,
List<Vector> means,
List<Vector> sums,
List<ModifiableDBIDs> clusters,
WritableIntegerDataStore assignment,
WritableDoubleDataStore upper,
WritableDataStore<double[]> lower)
Reassign objects, but only if their bounds indicate it is necessary to do
so.
|
private void |
KMeansElkan.updateBounds(Relation<V> relation,
WritableIntegerDataStore assignment,
WritableDoubleDataStore upper,
WritableDataStore<double[]> lower,
double[] move)
Update the bounds for k-means.
|
Modifier and Type | Field and Description |
---|---|
private WritableDataStore<long[]> |
HiSC.Instance.commonPreferenceVectors
Shared preference vectors.
|
private WritableDataStore<long[]> |
DiSH.Instance.commonPreferenceVectors
Shared preference vectors.
|
private WritableDataStore<long[]> |
DiSH.DiSHClusterOrder.commonPreferenceVectors
Preference vectors.
|
private WritableDataStore<long[]> |
DiSH.Instance.tmpPreferenceVectors
Temporary storage for new preference vectors.
|
Modifier and Type | Method and Description |
---|---|
private void |
P3C.assignUnassigned(Relation<V> relation,
WritableDataStore<double[]> probClusterIGivenX,
List<MultivariateGaussianModel> models,
ModifiableDBIDs unassigned)
Assign unassigned objects to best candidate based on shortest Mahalanobis
distance.
|
private void |
P3C.computeFuzzyMembership(Relation<V> relation,
ArrayList<P3C.Signature> clusterCores,
ModifiableDBIDs unassigned,
WritableDataStore<double[]> probClusterIGivenX,
List<MultivariateGaussianModel> models,
int dim)
Computes a fuzzy membership with the weights based on which cluster cores
each data point is part of.
|
private ArrayList<P3C.ClusterCandidate> |
P3C.hardClustering(WritableDataStore<double[]> probClusterIGivenX,
List<P3C.Signature> clusterCores,
DBIDs dbids)
Creates a hard clustering from the specified soft membership matrix.
|
Constructor and Description |
---|
DiSH.DiSHClusterOrder(String name,
String shortname,
ArrayModifiableDBIDs ids,
WritableDoubleDataStore reachability,
WritableDBIDDataStore predecessor,
WritableIntegerDataStore corrdim,
WritableDataStore<long[]> commonPreferenceVectors)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
private void |
DWOF.clusterData(DBIDs ids,
RangeQuery<O> rnnQuery,
WritableDoubleDataStore radii,
WritableDataStore<ModifiableDBIDs> labels)
This method applies a density based clustering algorithm.
|
private int |
DWOF.updateSizes(DBIDs ids,
WritableDataStore<ModifiableDBIDs> labels,
WritableIntegerDataStore newSizes)
This method updates each object's cluster size after the clustering step.
|
Modifier and Type | Method and Description |
---|---|
protected void |
INFLO.computeINFLO(Relation<O> relation,
ModifiableDBIDs pruned,
WritableDataStore<ModifiableDBIDs> knns,
WritableDataStore<ModifiableDBIDs> rnns,
WritableDoubleDataStore density,
WritableDoubleDataStore inflos,
DoubleMinMax inflominmax)
Compute the final INFLO scores.
|
protected void |
INFLO.computeINFLO(Relation<O> relation,
ModifiableDBIDs pruned,
WritableDataStore<ModifiableDBIDs> knns,
WritableDataStore<ModifiableDBIDs> rnns,
WritableDoubleDataStore density,
WritableDoubleDataStore inflos,
DoubleMinMax inflominmax)
Compute the final INFLO scores.
|
protected void |
INFLO.computeNeighborhoods(Relation<O> relation,
KNNQuery<O> knnQuery,
ModifiableDBIDs pruned,
WritableDataStore<ModifiableDBIDs> knns,
WritableDataStore<ModifiableDBIDs> rnns,
WritableDoubleDataStore density)
Compute neighborhoods
|
protected void |
INFLO.computeNeighborhoods(Relation<O> relation,
KNNQuery<O> knnQuery,
ModifiableDBIDs pruned,
WritableDataStore<ModifiableDBIDs> knns,
WritableDataStore<ModifiableDBIDs> rnns,
WritableDoubleDataStore density)
Compute neighborhoods
|
protected void |
KDEOS.computeOutlierScores(KNNQuery<O> knnq,
DBIDs ids,
WritableDataStore<double[]> densities,
WritableDoubleDataStore kdeos,
DoubleMinMax minmax)
Compute the final KDEOS scores.
|
protected void |
KDEOS.estimateDensities(Relation<O> rel,
KNNQuery<O> knnq,
DBIDs ids,
WritableDataStore<double[]> densities)
Perform the kernel density estimation step.
|
protected DBIDs |
INFLO.getKNN(DBIDIter q,
KNNQuery<O> knnQuery,
WritableDataStore<ModifiableDBIDs> knns,
WritableDoubleDataStore density)
Get the (forward only) kNN of an object, including the query point
|
protected void |
LOCI.precomputeInterestingRadii(DBIDs ids,
RangeQuery<O> rangeQuery,
WritableDataStore<LOCI.DoubleIntArrayList> interestingDistances)
Preprocessing step: determine the radii of interest for each point.
|
Modifier and Type | Interface and Description |
---|---|
interface |
WritableDBIDDataStore
Data store specialized for doubles.
|
interface |
WritableDoubleDataStore
Data store specialized for doubles.
|
interface |
WritableIntegerDataStore
Data store specialized for doubles.
|
Modifier and Type | Method and Description |
---|---|
<T> WritableDataStore<T> |
WritableRecordStore.getStorage(int col,
Class<? super T> datatype)
Get a
WritableDataStore instance for a particular record column. |
static <T> WritableDataStore<T> |
DataStoreUtil.makeStorage(DBIDs ids,
int hints,
Class<? super T> dataclass)
Make a new storage, to associate the given ids with an object of class
dataclass.
|
<T> WritableDataStore<T> |
DataStoreFactory.makeStorage(DBIDs ids,
int hints,
Class<? super T> dataclass)
Make a new storage, to associate the given ids with an object of class
dataclass.
|
Modifier and Type | Class and Description |
---|---|
class |
ArrayDBIDStore
A class to answer representation queries using the stored Array.
|
class |
ArrayDoubleStore
A class to answer representation queries using the stored Array.
|
class |
ArrayIntegerStore
A class to answer representation queries using the stored Array.
|
protected class |
ArrayRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
ArrayStore<T>
A class to answer representation queries using the stored Array.
|
class |
MapIntegerDBIDDBIDStore
Writable data store for double values.
|
class |
MapIntegerDBIDDoubleStore
Writable data store for double values.
|
class |
MapIntegerDBIDIntegerStore
Writable data store for double values.
|
protected class |
MapIntegerDBIDRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
MapIntegerDBIDStore<T>
A class to answer representation queries using a map.
|
protected class |
MapRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
MapStore<T>
A class to answer representation queries using a map.
|
Modifier and Type | Method and Description |
---|---|
<T> WritableDataStore<T> |
MapRecordStore.getStorage(int col,
Class<? super T> datatype) |
<T> WritableDataStore<T> |
MapIntegerDBIDRecordStore.getStorage(int col,
Class<? super T> datatype) |
<T> WritableDataStore<T> |
ArrayRecordStore.getStorage(int col,
Class<? super T> datatype) |
<T> WritableDataStore<T> |
MemoryDataStoreFactory.makeStorage(DBIDs ids,
int hints,
Class<? super T> dataclass) |
Modifier and Type | Field and Description |
---|---|
protected WritableDataStore<R> |
AbstractPreprocessorIndex.storage
The data store.
|
Modifier and Type | Field and Description |
---|---|
private WritableDataStore<TreeSet<DoubleDBIDPair>> |
MaterializeKNNAndRKNNPreprocessor.materialized_RkNN
Additional data storage for RkNN.
|
(package private) WritableDataStore<int[]> |
SpacefillingKNNPreprocessor.positions
Curve position storage
|
(package private) WritableDataStore<int[]> |
NaiveProjectedKNNPreprocessor.positions
Curve position storage
|
Modifier and Type | Field and Description |
---|---|
(package private) WritableDataStore<T> |
WriteDataStoreProcessor.store
Store to write to
|
Constructor and Description |
---|
WriteDataStoreProcessor(WritableDataStore<T> store)
Constructor.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.