Package | Description |
---|---|
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.data.projection |
Data projections.
|
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.database.relation |
Relations, materialized and virtual (views).
|
de.lmu.ifi.dbs.elki.datasource.filter.typeconversions |
Filters to perform data type conversions.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.set |
Distance functions for binary and set type data.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces.
|
de.lmu.ifi.dbs.elki.index.tree.spatial |
Tree-based index structures for spatial indexing.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn | |
de.lmu.ifi.dbs.elki.math.linearalgebra |
Linear Algebra package provides classes and computational methods for operations on matrices.
|
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike |
Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
|
Modifier and Type | Interface and Description |
---|---|
static interface |
FeatureVector.Factory<V extends FeatureVector<? extends D>,D>
Factory API for this feature vector.
|
Modifier and Type | Interface and Description |
---|---|
interface |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
interface |
SparseFeatureVector<D>
Extended interface for sparse feature vector types.
|
interface |
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractNumberVector
AbstractNumberVector is an abstract implementation of FeatureVector.
|
class |
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
class |
ByteVector
Vector using
byte[] storage. |
class |
DoubleVector
Vector type using
double[] storage for real numbers. |
class |
FloatVector
Vector type using
float[] storage, thus needing approximately half as
much memory as DoubleVector . |
class |
IntegerVector
Vector type using
int[] storage. |
class |
OneDimensionalDoubleVector
Specialized class implementing a one-dimensional double vector without using
an array.
|
class |
ShortVector
Vector type using
short[] storage. |
class |
SparseByteVector
Sparse vector type, using
byte[] for storing the values, and
int[] for storing the indexes, approximately 5 bytes per non-zero
value (limited to -128..+127). |
class |
SparseDoubleVector
Sparse vector type, using
double[] for storing the values, and
int[] for storing the indexes, approximately 12 bytes per non-zero
value. |
class |
SparseFloatVector
Sparse vector type, using
float[] for storing the values, and
int[] for storing the indexes, approximately 8 bytes per non-zero
value. |
class |
SparseIntegerVector
Sparse vector type, using
int[] for storing the values, and
int[] for storing the indexes, approximately 8 bytes per non-zero
integer value. |
class |
SparseShortVector
Sparse vector type, using
short[] for storing the values, and
int[] for storing the indexes, approximately 6 bytes per non-zero
value. |
Modifier and Type | Class and Description |
---|---|
class |
CorrelationModel<V extends FeatureVector<?>>
Cluster model using a filtered PCA result and an centroid.
|
Modifier and Type | Field and Description |
---|---|
private V |
CorrelationModel.centroid
The centroid of this cluster.
|
Modifier and Type | Class and Description |
---|---|
class |
FeatureSelection<V extends FeatureVector<F>,F>
Projection class for number vectors.
|
static class |
FeatureSelection.Parameterizer<V extends FeatureVector<F>,F>
Parameterization class.
|
Modifier and Type | Method and Description |
---|---|
private static <V extends FeatureVector<F>,F> |
FeatureSelection.getAdapter(FeatureVector.Factory<V,F> factory)
Choose the best adapter for this.
|
Modifier and Type | Class and Description |
---|---|
class |
MultivariateSeriesTypeInformation<V extends FeatureVector<?>>
Type information for multi-variate time series.
|
class |
VectorFieldTypeInformation<V extends FeatureVector<?>>
Type information to specify that a type has a fixed dimensionality.
|
class |
VectorTypeInformation<V extends FeatureVector<?>>
Construct a type information for vector spaces with fixed dimensionality.
|
Modifier and Type | Field and Description |
---|---|
static VectorTypeInformation<FeatureVector<?>> |
TypeUtil.FEATURE_VECTORS
Any feature vector type.
|
Modifier and Type | Method and Description |
---|---|
static <V extends FeatureVector<?>> |
VectorTypeInformation.typeRequest(Class<? super V> cls)
Constructor for a type request without dimensionality constraints.
|
static <V extends FeatureVector<?>> |
VectorFieldTypeInformation.typeRequest(Class<? super V> cls)
Constructor for a type request without dimensionality constraints.
|
static <V extends FeatureVector<?>> |
MultivariateSeriesTypeInformation.typeRequest(Class<? super V> cls)
Constructor for a type request without dimensionality constraints.
|
static <V extends FeatureVector<?>> |
VectorTypeInformation.typeRequest(Class<? super V> cls,
int mindim,
int maxdim)
Constructor for a type request with dimensionality constraints.
|
static <V extends FeatureVector<?>> |
VectorFieldTypeInformation.typeRequest(Class<? super V> cls,
int mindim,
int maxdim)
Constructor for a type request with dimensionality constraints.
|
Modifier and Type | Interface and Description |
---|---|
interface |
DiscreteUncertainObject
Interface for discrete uncertain objects, that are represented by a finite
(possibly weighted) number of samples.
|
interface |
UncertainObject
Interface for uncertain objects.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractUncertainObject
Abstract base implementation for
UncertainObject s, providing shared
functionality such as bounding box access and random generation. |
class |
SimpleGaussianContinuousUncertainObject
Gaussian model for uncertain objects, sampled from a 3-sigma bounding box.
|
class |
UniformContinuousUncertainObject
Continuous uncertain object model using a uniform distribution on the
bounding box.
|
class |
UnweightedDiscreteUncertainObject
Unweighted implementation of discrete uncertain objects.
|
class |
WeightedDiscreteUncertainObject
Weighted version of discrete uncertain objects.
|
Modifier and Type | Method and Description |
---|---|
static <V extends FeatureVector<?>> |
RelationUtil.assumeVectorField(Relation<V> relation)
Get the vector field type information from a relation.
|
Modifier and Type | Class and Description |
---|---|
class |
MultivariateTimeSeriesFilter<V extends FeatureVector<?>>
Class to "fold" a flat number vector into a multivariate time series.
|
static class |
MultivariateTimeSeriesFilter.Parameterizer<V extends FeatureVector<?>>
Parameterization class.
|
Modifier and Type | Class and Description |
---|---|
class |
JaccardSimilarityDistanceFunction<O extends FeatureVector<?>>
A flexible extension of Jaccard similarity to non-binary vectors.
|
Modifier and Type | Method and Description |
---|---|
SimpleTypeInformation<? super FeatureVector<?>> |
HammingDistanceFunction.getInputTypeRestriction() |
Modifier and Type | Method and Description |
---|---|
double |
HammingDistanceFunction.distance(FeatureVector<?> o1,
FeatureVector<?> o2) |
double |
HammingDistanceFunction.distance(FeatureVector<?> o1,
FeatureVector<?> o2) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractDimensionsSelectingDistanceFunction<V extends FeatureVector<?>>
Abstract base class for distances computed only in subspaces.
|
Modifier and Type | Class and Description |
---|---|
class |
SpatialPointLeafEntry
Represents an entry in a leaf node of a spatial index.
|
Modifier and Type | Class and Description |
---|---|
class |
DeLiCluLeafEntry
Defines the requirements for a leaf entry in an DeLiClu-Tree node.
|
Modifier and Type | Class and Description |
---|---|
class |
RdKNNLeafEntry
Represents an entry in a leaf node of an RdKNN-Tree.
|
Modifier and Type | Class and Description |
---|---|
class |
Centroid
Class to compute the centroid of some data.
|
class |
ProjectedCentroid
Centroid only using a subset of dimensions.
|
class |
Vector
A mathematical vector object, along with mathematical operations.
|
Modifier and Type | Method and Description |
---|---|
static <F> FeatureVectorAdapter<F> |
ArrayLikeUtil.featureVectorAdapter(FeatureVector<F> prototype)
Get the static instance.
|
F |
FeatureVectorAdapter.get(FeatureVector<F> array,
int off) |
int |
FeatureVectorAdapter.size(FeatureVector<F> array) |
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.