Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.database.ids |
Database object identification and ID group handling API.
|
de.lmu.ifi.dbs.elki.database.ids.integer |
Integer-based DBID implementation --
do not use directly - always use
DBIDUtil . |
de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments |
Pair-segment analysis of multiple clusterings.
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
Modifier and Type | Class and Description |
---|---|
static class |
COPACNeighborPredicate.COPACModel
Model used by COPAC for core point property.
|
Modifier and Type | Field and Description |
---|---|
(package private) SetDBIDs |
PreDeConNeighborPredicate.PreDeConModel.ids
Neighbor ids.
|
(package private) SetDBIDs |
COPACNeighborPredicate.COPACModel.ids
Neighbor ids.
|
Constructor and Description |
---|
COPACModel(int cdim,
SetDBIDs ids)
COPAC model.
|
PreDeConModel(int pdim,
SetDBIDs ids)
PreDeCon model.
|
Modifier and Type | Method and Description |
---|---|
private SetDBIDs[][] |
P3C.partitionData(Relation<V> relation,
int bins)
Partition the data set into
bins bins in each dimension
independently. |
Modifier and Type | Method and Description |
---|---|
private int |
P3C.chiSquaredUniformTest(SetDBIDs[] parts,
long[] marked,
int card)
Performs a ChiSquared test to determine whether an attribute has a uniform
distribution.
|
private ArrayList<P3C.Signature> |
P3C.constructOneSignatures(SetDBIDs[][] partitions,
long[][] markers)
Construct the 1-signatures by merging adjacent dense bins.
|
Modifier and Type | Interface and Description |
---|---|
interface |
DBID
Database ID object.
|
interface |
DBIDVar
(Persistent) variable storing a DBID reference.
|
interface |
HashSetDBIDs
Hash-organized DBIDs
|
interface |
HashSetModifiableDBIDs
Set-oriented implementation of a modifiable DBID collection.
|
Modifier and Type | Class and Description |
---|---|
class |
EmptyDBIDs
Empty DBID collection.
|
Modifier and Type | Method and Description |
---|---|
static SetDBIDs |
DBIDUtil.ensureSet(DBIDs ids)
Ensure that the given DBIDs support fast "contains" operations.
|
Modifier and Type | Class and Description |
---|---|
(package private) class |
IntegerDBID
Database ID object.
|
(package private) class |
IntegerDBIDRange
Representing a DBID range allocation.
|
(package private) class |
IntegerDBIDVar
Variable for storing a single DBID reference.
|
(package private) class |
TroveHashSetModifiableDBIDs
Implementation using GNU Trove Int Hash Sets.
|
Modifier and Type | Method and Description |
---|---|
private void |
Segments.recursivelyFill(List<List<? extends Cluster<?>>> cs,
int depth,
SetDBIDs first,
SetDBIDs second,
int[] path,
boolean objectsegment) |
Modifier and Type | Method and Description |
---|---|
private XYCurve |
OutlierPrecisionRecallCurve.computePrecisionResult(int size,
SetDBIDs ids,
DBIDIter iter,
DoubleRelation scores) |
private XYCurve |
OutlierPrecisionAtKCurve.computePrecisionResult(int size,
SetDBIDs positiveids,
DBIDs order) |
private OutlierROCCurve.ROCResult |
OutlierROCCurve.computeROCResult(int size,
SetDBIDs positiveids,
DBIDs order) |
private OutlierROCCurve.ROCResult |
OutlierROCCurve.computeROCResult(int size,
SetDBIDs positiveids,
OutlierResult or) |
private OutlierSmROCCurve.SmROCResult |
OutlierSmROCCurve.computeSmROCResult(SetDBIDs positiveids,
OutlierResult or) |
private EvaluationResult |
OutlierRankingEvaluation.evaluateOrderingResult(int size,
SetDBIDs positiveids,
DBIDs order) |
private EvaluationResult |
OutlierRankingEvaluation.evaluateOutlierResult(int size,
SetDBIDs positiveids,
OutlierResult or) |
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.