Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.database |
ELKI database layer - loading, storing, indexing and accessing data
|
de.lmu.ifi.dbs.elki.distance.similarityfunction |
Similarity functions.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel |
Kernel functions.
|
Modifier and Type | Field and Description |
---|---|
private SimilarityFunction<V,D> |
SOD.similarityFunction
The similarity function
SOD.SIM_ID . |
private SimilarityFunction<V,D> |
SOD.Parameterizer.similarityFunction
The similarity function -
SOD.SIM_ID . |
Constructor and Description |
---|
SOD(int knn,
double alpha,
SimilarityFunction<V,D> similarityFunction)
Constructor with parameters.
|
Modifier and Type | Method and Description |
---|---|
static <O,D extends Distance<D>> |
QueryUtil.getSimilarityQuery(Database database,
SimilarityFunction<? super O,D> similarityFunction,
Object... hints)
Get a similarity query, automatically choosing a relation.
|
<O,D extends Distance<D>> |
AbstractDatabase.getSimilarityQuery(Relation<O> objQuery,
SimilarityFunction<? super O,D> similarityFunction,
Object... hints) |
<O,D extends Distance<D>> |
Database.getSimilarityQuery(Relation<O> relation,
SimilarityFunction<? super O,D> similarityFunction,
Object... hints)
Get the similarity query for a particular similarity function.
|
Modifier and Type | Interface and Description |
---|---|
interface |
DBIDSimilarityFunction<D extends Distance<D>>
Interface DBIDSimilarityFunction describes the requirements of any similarity
function defined over object IDs.
|
interface |
IndexBasedSimilarityFunction<O,D extends Distance<D>>
Interface for preprocessor/index based similarity functions.
|
interface |
NormalizedPrimitiveSimilarityFunction<O,D extends Distance<D>>
Marker interface for similarity functions working on primitive objects, and
limited to the 0-1 value range.
|
interface |
NormalizedSimilarityFunction<O,D extends Distance<?>>
Marker interface to signal that the similarity function is normalized to
produce values in the range of [0:1].
|
interface |
PrimitiveSimilarityFunction<O,D extends Distance<D>>
Interface SimilarityFunction describes the requirements of any similarity
function.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractDBIDSimilarityFunction<D extends Distance<D>>
Abstract super class for distance functions needing a preprocessor.
|
class |
AbstractIndexBasedSimilarityFunction<O,I extends Index,R,D extends Distance<D>>
Abstract super class for distance functions needing a preprocessor.
|
class |
AbstractPrimitiveSimilarityFunction<O,D extends Distance<D>>
Base implementation of a similarity function.
|
class |
FractionalSharedNearestNeighborSimilarityFunction<O>
SharedNearestNeighborSimilarityFunction with a pattern defined to accept
Strings that define a non-negative Integer.
|
class |
InvertedDistanceSimilarityFunction<O>
Adapter to use a primitive number-distance as similarity measure, by computing
1/distance.
|
class |
SharedNearestNeighborSimilarityFunction<O>
SharedNearestNeighborSimilarityFunction with a pattern defined to accept
Strings that define a non-negative Integer.
|
Modifier and Type | Class and Description |
---|---|
class |
FooKernelFunction
Provides an experimental KernelDistanceFunction for NumberVectors.
|
class |
LinearKernelFunction<O extends NumberVector<?>>
Provides a linear Kernel function that computes a similarity between the two
feature vectors V1 and V2 defined by V1^T*V2.
|
class |
PolynomialKernelFunction
Provides a polynomial Kernel function that computes a similarity between the
two feature vectors V1 and V2 defined by (V1^T*V2)^degree.
|