| Modifier and Type | Class and Description |
|---|---|
class |
AbstractSpatialDoubleDistanceFunction
Abstract base class for typical distance functions that allow
rectangle-to-rectangle lower bounds.
|
class |
AbstractSpatialDoubleDistanceNorm
Abstract base class for typical distance functions that allow
rectangle-to-rectangle lower bounds.
|
class |
AbstractVectorDoubleDistanceFunction
Abstract base class for the most common family of distance functions: defined
on number vectors and returning double values.
|
class |
AbstractVectorDoubleDistanceNorm
Abstract base class for double-valued number-vector-based distances based on
norms.
|
class |
ArcCosineDistanceFunction
Cosine distance function for feature vectors.
|
class |
BrayCurtisDistanceFunction
Bray-Curtis distance function / Sørensen–Dice coefficient for continuous
spaces.
|
class |
CanberraDistanceFunction
Canberra distance function, a variation of Manhattan distance.
|
class |
ClarkDistanceFunction
Clark distance function for vector spaces.
|
class |
CosineDistanceFunction
Cosine distance function for feature vectors.
|
class |
JeffreyDivergenceDistanceFunction
Provides the Jeffrey Divergence Distance for FeatureVectors.
|
class |
Kulczynski1DistanceFunction
Kulczynski similarity 1, in distance form.
|
class |
LorentzianDistanceFunction
Lorentzian distance function for vector spaces.
|
class |
WeightedDistanceFunction
Provides the Weighted distance for feature vectors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
HistogramIntersectionDistanceFunction
Intersection distance for color histograms.
|
class |
HSBHistogramQuadraticDistanceFunction
Distance function for HSB color histograms based on a quadratic form and
color similarity.
|
class |
RGBHistogramQuadraticDistanceFunction
Distance function for RGB color histograms based on a quadratic form and
color similarity.
|
| Modifier and Type | Class and Description |
|---|---|
class |
PearsonCorrelationDistanceFunction
Pearson correlation distance function for feature vectors.
|
class |
SquaredPearsonCorrelationDistanceFunction
Squared Pearson correlation distance function for feature vectors.
|
class |
WeightedPearsonCorrelationDistanceFunction
Pearson correlation distance function for feature vectors.
|
class |
WeightedSquaredPearsonCorrelationDistanceFunction
Squared Pearson correlation distance function for feature vectors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
DimensionSelectingLatLngDistanceFunction
Distance function for 2D vectors in Latitude, Longitude form.
|
class |
LatLngDistanceFunction
Distance function for 2D vectors in Latitude, Longitude form.
|
class |
LngLatDistanceFunction
Distance function for 2D vectors in Longitude, Latitude form.
|
| Modifier and Type | Class and Description |
|---|---|
class |
EuclideanDistanceFunction
Provides the Euclidean distance for FeatureVectors.
|
class |
LPNormDistanceFunction
Provides a LP-Norm for FeatureVectors.
|
class |
ManhattanDistanceFunction
Manhattan distance function to compute the Manhattan distance for a pair of
FeatureVectors.
|
class |
MaximumDistanceFunction
Maximum distance function to compute the Maximum distance for a pair of
FeatureVectors.
|
class |
MinimumDistanceFunction
Maximum distance function to compute the Minimum distance for a pair of
FeatureVectors.
|
class |
SparseEuclideanDistanceFunction
Euclidean distance function.
|
class |
SparseLPNormDistanceFunction
Provides a LP-Norm for FeatureVectors.
|
class |
SparseManhattanDistanceFunction
Manhattan distance function.
|
class |
SparseMaximumDistanceFunction
Maximum distance function.
|
class |
SquaredEuclideanDistanceFunction
Provides the squared Euclidean distance for FeatureVectors.
|
class |
WeightedLPNormDistanceFunction
Weighted version of the Euclidean distance function.
|
class |
WeightedSquaredEuclideanDistanceFunction
Provides the squared Euclidean distance for FeatureVectors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LevenshteinDistanceFunction
Classic Levenshtein distance on strings.
|
class |
NormalizedLevenshteinDistanceFunction
Levenshtein distance on strings, normalized by string length.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractDimensionsSelectingDoubleDistanceFunction<V extends FeatureVector<?>>
Provides a distance function that computes the distance (which is a double
distance) between feature vectors only in specified dimensions.
|
class |
DimensionSelectingDistanceFunction
Provides a distance function that computes the distance between feature
vectors as the absolute difference of their values in a specified dimension.
|
class |
SubspaceEuclideanDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|
class |
SubspaceLPNormDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|
class |
SubspaceManhattanDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractEditDistanceFunction
Provides the Edit Distance for FeatureVectors.
|
class |
DTWDistanceFunction
Provides the Dynamic Time Warping distance for FeatureVectors.
|
class |
EDRDistanceFunction
Provides the Edit Distance on Real Sequence distance for FeatureVectors.
|
class |
ERPDistanceFunction
Provides the Edit Distance With Real Penalty distance for FeatureVectors.
|
class |
LCSSDistanceFunction
Provides the Longest Common Subsequence distance for FeatureVectors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
FooKernelFunction
Provides an experimental KernelDistanceFunction for NumberVectors.
|
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.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MultiLPNorm
Tutorial example for ELKI.
|
class |
TutorialDistanceFunction
Tutorial example for ELKI.
|