Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain |
Clustering algorithms for uncertain data.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms.
|
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.data.type |
Data type information, also used for type restrictions.
|
de.lmu.ifi.dbs.elki.data.uncertain |
Uncertain data objects.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
|
de.lmu.ifi.dbs.elki.evaluation.histogram |
Functionality for the evaluation of algorithms using histograms.
|
Modifier and Type | Method and Description |
---|---|
protected Clustering<?> |
RepresentativeUncertainClustering.runClusteringAlgorithm(ResultHierarchy hierarchy,
Result parent,
DBIDs ids,
DataStore<DoubleVector> store,
int dim,
String title)
Run a clustering algorithm on a single instance.
|
protected C |
CenterOfMassMetaClustering.runClusteringAlgorithm(ResultHierarchy hierarchy,
Result parent,
DBIDs ids,
DataStore<DoubleVector> store,
int dim,
String title)
Run a clustering algorithm on a single instance.
|
Modifier and Type | Method and Description |
---|---|
HistogramResult<DoubleVector> |
EvaluateRankingQuality.run(Database database) |
HistogramResult<DoubleVector> |
DistanceStatisticsWithClasses.run(Database database) |
HistogramResult<DoubleVector> |
RankingQualityHistogram.run(Database database,
Relation<O> relation)
Process a database
|
CollectionResult<DoubleVector> |
AveragePrecisionAtK.run(Database database,
Relation<O> relation,
Relation<?> lrelation)
Run the algorithm
|
Modifier and Type | Field and Description |
---|---|
static ByteBufferSerializer<DoubleVector> |
DoubleVector.BYTE_SERIALIZER
Serializer for up to 127 dimensions.
|
static ByteBufferSerializer<DoubleVector> |
DoubleVector.SHORT_SERIALIZER
Serializer for up to 2^15-1 dimensions.
|
static ByteBufferSerializer<DoubleVector> |
DoubleVector.VARIABLE_SERIALIZER
Serializer using varint encoding.
|
Modifier and Type | Method and Description |
---|---|
DoubleVector |
DoubleVector.SmallSerializer.fromByteBuffer(ByteBuffer buffer) |
DoubleVector |
DoubleVector.ShortSerializer.fromByteBuffer(ByteBuffer buffer) |
DoubleVector |
DoubleVector.VariableSerializer.fromByteBuffer(ByteBuffer buffer) |
<A> DoubleVector |
DoubleVector.Factory.newFeatureVector(A array,
ArrayAdapter<? extends Number,A> adapter) |
<A> DoubleVector |
DoubleVector.Factory.newNumberVector(A array,
NumberArrayAdapter<?,? super A> adapter) |
DoubleVector |
DoubleVector.Factory.newNumberVector(double[] values) |
Modifier and Type | Method and Description |
---|---|
ByteBufferSerializer<DoubleVector> |
DoubleVector.Factory.getDefaultSerializer() |
Class<? super DoubleVector> |
DoubleVector.Factory.getRestrictionClass() |
Modifier and Type | Method and Description |
---|---|
int |
DoubleVector.SmallSerializer.getByteSize(DoubleVector vec) |
int |
DoubleVector.ShortSerializer.getByteSize(DoubleVector vec) |
int |
DoubleVector.VariableSerializer.getByteSize(DoubleVector vec) |
void |
DoubleVector.SmallSerializer.toByteBuffer(ByteBuffer buffer,
DoubleVector vec) |
void |
DoubleVector.ShortSerializer.toByteBuffer(ByteBuffer buffer,
DoubleVector vec) |
void |
DoubleVector.VariableSerializer.toByteBuffer(ByteBuffer buffer,
DoubleVector vec) |
Modifier and Type | Field and Description |
---|---|
static VectorFieldTypeInformation<DoubleVector> |
TypeUtil.DOUBLE_VECTOR_FIELD
Input type for algorithms that require number vector fields.
|
Modifier and Type | Field and Description |
---|---|
private DoubleVector[] |
WeightedDiscreteUncertainObject.samples
Samples
|
private DoubleVector[] |
UnweightedDiscreteUncertainObject.samples
Sample vectors.
|
Modifier and Type | Method and Description |
---|---|
DoubleVector |
WeightedDiscreteUncertainObject.drawSample(Random rand) |
DoubleVector |
UnweightedDiscreteUncertainObject.drawSample(Random rand) |
DoubleVector |
UniformContinuousUncertainObject.drawSample(Random rand) |
DoubleVector |
UncertainObject.drawSample(Random rand)
Draw a random sampled instance.
|
DoubleVector |
SimpleGaussianContinuousUncertainObject.drawSample(Random rand) |
abstract DoubleVector |
AbstractUncertainObject.drawSample(Random rand) |
DoubleVector |
WeightedDiscreteUncertainObject.getCenterOfMass() |
DoubleVector |
UnweightedDiscreteUncertainObject.getCenterOfMass() |
DoubleVector |
UniformContinuousUncertainObject.getCenterOfMass() |
DoubleVector |
UncertainObject.getCenterOfMass()
Get the center of mass of the uncertain object.
|
DoubleVector |
SimpleGaussianContinuousUncertainObject.getCenterOfMass() |
abstract DoubleVector |
AbstractUncertainObject.getCenterOfMass() |
DoubleVector |
WeightedDiscreteUncertainObject.getSample(int i) |
DoubleVector |
UnweightedDiscreteUncertainObject.getSample(int i) |
DoubleVector |
DiscreteUncertainObject.getSample(int i)
Get the i'th vector.
|
Constructor and Description |
---|
UnweightedDiscreteUncertainObject(DoubleVector[] samples)
Constructor.
|
WeightedDiscreteUncertainObject(DoubleVector[] samples,
double[] weights)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
protected NumberVectorRandomFeatureSelectionFilter<DoubleVector> |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.makeInstance() |
protected NumberVectorFeatureSelectionFilter<DoubleVector> |
NumberVectorFeatureSelectionFilter.Parameterizer.makeInstance() |
protected HistogramJitterFilter<DoubleVector> |
HistogramJitterFilter.Parameterizer.makeInstance() |
Modifier and Type | Method and Description |
---|---|
HistogramResult<DoubleVector> |
ComputeOutlierHistogram.evaluateOutlierResult(Database database,
OutlierResult or)
Evaluate a single outlier result as histogram.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.