Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering |
Biclustering algorithms
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de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical |
Hierarchical agglomerative clustering (HAC).
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de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction |
Extraction of partitional clusterings from hierarchical results.
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de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations
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de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization |
Initialization strategies for k-means.
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de.lmu.ifi.dbs.elki.algorithm.clustering.optics |
OPTICS family of clustering algorithms.
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de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased |
Angle-based outlier detection algorithms.
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de.lmu.ifi.dbs.elki.algorithm.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
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de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic |
Outlier detection algorithms based on intrinsic dimensionality.
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de.lmu.ifi.dbs.elki.algorithm.projection |
Data projections (see also preprocessing filters for basic projections).
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de.lmu.ifi.dbs.elki.algorithm.timeseries |
Algorithms for change point detection in time series.
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de.lmu.ifi.dbs.elki.database.ids |
Database object identification and ID group handling API.
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de.lmu.ifi.dbs.elki.database.ids.integer |
Integer-based DBID implementation --
do not use directly - always use
DBIDUtil . |
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel |
Kernel functions.
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de.lmu.ifi.dbs.elki.index.tree.spatial.kd |
K-d-tree and variants
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Modifier and Type | Field and Description |
---|---|
private DBIDArrayIter |
AbstractBiclustering.iter
Iterator to use for more efficient random access.
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Modifier and Type | Field and Description |
---|---|
DBIDArrayIter |
MatrixParadigm.ix
Two iterators to reference to objects.
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DBIDArrayIter |
MatrixParadigm.iy
Two iterators to reference to objects.
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private DBIDArrayIter |
AbstractHDBSCAN.HDBSCANAdapter.p
Iterators for accessing the data objects.
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private DBIDArrayIter |
AbstractHDBSCAN.HDBSCANAdapter.q
Iterators for accessing the data objects.
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Modifier and Type | Method and Description |
---|---|
private void |
CLINK.clinkstep3(DBIDRef id,
DBIDArrayIter i,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
Third step: Determine the values for P and L
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private void |
CLINK.clinkstep4567(DBIDRef id,
ArrayDBIDs ids,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
Fourth to seventh step of CLINK: find best insertion
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private void |
CLINK.clinkstep8(DBIDRef id,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
Update hierarchy.
|
static int |
NNChain.findUnlinked(int pos,
int end,
DBIDArrayIter ix,
PointerHierarchyRepresentationBuilder builder)
Find an unlinked object.
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protected void |
CLINK.process(DBIDRef id,
ArrayDBIDs ids,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
CLINK main loop, based on the SLINK main loop.
|
protected void |
SLINK.process(DBIDRef id,
ArrayDBIDs ids,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
SLINK main loop.
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protected static int |
AGNES.shrinkActiveSet(DBIDArrayIter ix,
PointerHierarchyRepresentationBuilder builder,
int end,
int x)
Shrink the active set: if the last x objects are all merged, we can reduce
the working size accordingly.
|
private void |
SLINK.slinkstep3(DBIDRef id,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda,
WritableDoubleDataStore m)
Third step: Determine the values for P and L
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private void |
SLINK.slinkstep4(DBIDRef id,
DBIDArrayIter it,
int n,
WritableDBIDDataStore pi,
WritableDoubleDataStore lambda)
Fourth step: Actualize the clusters if necessary
|
private void |
SLINK.step2(DBIDRef id,
DBIDArrayIter it,
int n,
DistanceQuery<? super O> distQuery,
WritableDoubleDataStore m)
Second step: Determine the pairwise distances from all objects in the
pointer representation to the new object with the specified id.
|
private void |
SLINK.step2primitive(DBIDRef id,
DBIDArrayIter it,
int n,
Relation<? extends O> relation,
PrimitiveDistanceFunction<? super O> distFunc,
WritableDoubleDataStore m)
Second step: Determine the pairwise distances from all objects in the
pointer representation to the new object with the specified id.
|
protected void |
AnderbergHierarchicalClustering.updateMatrix(int size,
double[] scratch,
DBIDArrayIter ij,
double[] bestd,
int[] besti,
PointerHierarchyRepresentationBuilder builder,
double mindist,
int x,
int y,
int sizex,
int sizey)
Update the scratch distance matrix.
|
Modifier and Type | Method and Description |
---|---|
private Clustering<DendrogramModel> |
AbstractCutDendrogram.Instance.buildFlat(DBIDArrayIter it,
int split,
FiniteProgress progress)
Build a flat clustering.
|
private Clustering<DendrogramModel> |
AbstractCutDendrogram.Instance.buildHierarchical(DBIDArrayIter it,
int split,
FiniteProgress progress)
Build a hierarchical clustering.
|
private void |
AbstractCutDendrogram.Instance.buildLeafClusters(DBIDArrayIter it,
int split,
FiniteProgress progress)
Prepare the leaf clusters by executing the first (size - 1 - split)
merges.
|
protected int |
CutDendrogramByNumberOfClusters.Instance.findSplit(DBIDArrayIter it) |
protected int |
CutDendrogramByHeight.Instance.findSplit(DBIDArrayIter it) |
protected abstract int |
AbstractCutDendrogram.Instance.findSplit(DBIDArrayIter it)
Find the splitting point in the ordered DBIDs list.
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Modifier and Type | Method and Description |
---|---|
protected double |
KMedoidsPark.assignToNearestCluster(DBIDArrayIter miter,
double[] dsum,
java.util.List<? extends ModifiableDBIDs> clusters,
DistanceQuery<V> distQ)
Returns a list of clusters.
|
protected void |
KMedoidsFastPAM.Instance.findBestSwaps(DBIDArrayIter m,
ArrayModifiableDBIDs bestids,
double[] best,
double[] cost)
Find the best swaps.
|
protected void |
KMedoidsFastPAM1.Instance.updateAssignment(ArrayModifiableDBIDs medoids,
DBIDArrayIter miter,
DBIDRef h,
int m)
Update an existing cluster assignment.
|
private int |
KMedoidsFastPAM1.Instance.updateSecondNearest(DBIDRef j,
DBIDArrayIter medoids,
int h,
double dist_h,
int n)
Find the second nearest medoid.
|
Modifier and Type | Method and Description |
---|---|
protected static double |
LABInitialMeans.getMinDist(DBIDArrayIter j,
DistanceQuery<?> distQ,
DBIDArrayIter mi,
WritableDoubleDataStore mindist)
Get the minimum distance to previous medoids.
|
Modifier and Type | Field and Description |
---|---|
private DBIDArrayIter |
OPTICSXi.SteepScanPosition.cur
Variable for accessing.
|
private DBIDArrayIter |
OPTICSXi.SteepScanPosition.next
Variable for accessing.
|
Modifier and Type | Method and Description |
---|---|
DBIDArrayIter |
ClusterOrder.iter()
Get an iterator.
|
Modifier and Type | Method and Description |
---|---|
protected double |
ABOD.computeABOF(KernelMatrix kernelMatrix,
DBIDRef pA,
DBIDArrayIter pB,
DBIDArrayIter pC,
MeanVariance s)
Compute the exact ABOF value.
|
Modifier and Type | Method and Description |
---|---|
static void |
SOS.nominateNeighbors(DBIDIter ignore,
DBIDArrayIter di,
double[] p,
double norm,
WritableDoubleDataStore scores)
Vote for neighbors not being outliers.
|
static double |
SOS.sumOfProbabilities(DBIDIter ignore,
DBIDArrayIter di,
double[] p)
Compute the sum of probabilities, stop at first 0, ignore query object.
|
Modifier and Type | Method and Description |
---|---|
static void |
ISOS.nominateNeighbors(DBIDIter ignore,
DBIDArrayIter di,
double[] p,
double norm,
WritableDoubleDataStore scores)
Vote for neighbors not being outliers.
|
Modifier and Type | Method and Description |
---|---|
DBIDArrayIter |
DenseAffinityMatrix.iterDBIDs() |
DBIDArrayIter |
SparseAffinityMatrix.iterDBIDs() |
DBIDArrayIter |
AffinityMatrix.iterDBIDs()
Array iterator over the stored objects.
|
Modifier and Type | Field and Description |
---|---|
(package private) DBIDArrayIter |
OfflineChangePointDetectionAlgorithm.Instance.iter
Iterator to reference data positions.
|
Modifier and Type | Interface and Description |
---|---|
interface |
DBIDArrayMIter
Modifiable array iterator.
|
interface |
DoubleDBIDListIter
Iterator over double-DBID pairs results.
|
interface |
DoubleDBIDListMIter
Modifiable DBIDList iterator.
|
Modifier and Type | Class and Description |
---|---|
protected static class |
EmptyDBIDs.EmptyDBIDIterator
Iterator for empty DBIDs-
|
Modifier and Type | Method and Description |
---|---|
DBIDArrayIter |
DBIDArrayIter.advance() |
DBIDArrayIter |
DBIDArrayIter.advance(int count) |
DBIDArrayIter |
ArrayDBIDs.iter()
Iterable
|
DBIDArrayIter |
DBIDArrayIter.retract() |
DBIDArrayIter |
DBIDArrayIter.seek(int off) |
Modifier and Type | Method and Description |
---|---|
private static void |
QuickSelectDBIDs.insertionSort(ArrayModifiableDBIDs data,
java.util.Comparator<? super DBIDRef> comparator,
int start,
int end,
DBIDArrayIter iter1,
DBIDArrayIter iter2)
Sort a small array using repetitive insertion sort.
|
Modifier and Type | Interface and Description |
---|---|
interface |
DoubleIntegerDBIDListIter
Combination interface of the DoubleDBIDListIter with IntegerDBIDIter.
|
(package private) interface |
DoubleIntegerDBIDListMIter
Combination interface for modifiable iterators.
|
(package private) interface |
IntegerDBIDArrayIter
Modifiable integer array iterator.
|
(package private) interface |
IntegerDBIDArrayMIter
Modifiable integer array iterator.
|
Modifier and Type | Class and Description |
---|---|
private class |
ArrayModifiableIntegerDBIDs.Itr
Iterator class.
|
private class |
ArrayModifiableIntegerDBIDs.Slice.SliceItr
Iterator class.
|
protected class |
ArrayStaticIntegerDBIDs.Itr
DBID iterator in ELKI/C style.
|
private class |
ArrayStaticIntegerDBIDs.Slice.SliceItr
Iterator class.
|
private class |
DoubleIntegerDBIDArrayList.Itr
List iterator.
|
private class |
DoubleIntegerDBIDKNNHeap.UnorderedIter
Iterate over all objects in the heap, not ordered.
|
private class |
DoubleIntegerDBIDSubList.Itr
Iterator for the sublist.
|
protected class |
IntegerDBID.Itr
Pseudo iterator for DBIDs interface.
|
private class |
IntegerDBIDKNNSubList.Itr
Iterator for the sublist.
|
private static class |
IntegerDBIDPair.Itr
Iterator.
|
private class |
IntegerDBIDPair.Slice.SliceItr
Iterator class.
|
private static class |
IntegerDBIDRange.Itr
Iterator in ELKI/C++ style.
|
protected class |
IntegerDBIDVar.Itr
Pseudo iterator for DBIDs interface.
|
private class |
UnmodifiableIntegerArrayDBIDs.Itr
Make an existing DBIDMIter unmodifiable.
|
Modifier and Type | Method and Description |
---|---|
DBIDArrayIter |
UnmodifiableIntegerArrayDBIDs.Itr.advance() |
DBIDArrayIter |
IntegerDBIDPair.Itr.advance(int count) |
DBIDArrayIter |
UnmodifiableIntegerArrayDBIDs.Itr.advance(int count) |
DBIDArrayIter |
IntegerDBIDPair.Itr.retract() |
DBIDArrayIter |
UnmodifiableIntegerArrayDBIDs.Itr.retract() |
DBIDArrayIter |
IntegerDBIDPair.Itr.seek(int off) |
DBIDArrayIter |
UnmodifiableIntegerArrayDBIDs.Itr.seek(int off) |
Modifier and Type | Method and Description |
---|---|
DBIDArrayIter |
KernelMatrix.DBIDMap.iter()
Get an array iterator, for scanning.
|
DBIDArrayIter |
KernelMatrix.RangeMap.iter() |
DBIDArrayIter |
KernelMatrix.SortedArrayMap.iter() |
Modifier and Type | Method and Description |
---|---|
private double |
MinimalisticMemoryKDTree.KDTreeKNNQuery.kdKNNSearch(int left,
int right,
int axis,
O query,
KNNHeap knns,
DBIDArrayIter iter,
double maxdist)
Perform a kNN search on the kd-tree.
|
private void |
MinimalisticMemoryKDTree.KDTreeRangeQuery.kdRangeSearch(int left,
int right,
int axis,
O query,
ModifiableDoubleDBIDList res,
DBIDArrayIter iter,
double radius)
Perform a kNN search on the kd-tree.
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Copyright © 2019 ELKI Development Team. License information.