| 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. similarityFunctionThe similarity function  SOD.SIM_ID. | 
| private SimilarityFunction<V,D> | SOD.Parameterizer. similarityFunctionThe 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  | FooKernelFunctionProvides 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  | PolynomialKernelFunctionProvides a polynomial Kernel function that computes a similarity between the
 two feature vectors V1 and V2 defined by (V1^T*V2)^degree. |