Package | Description |
---|---|
de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram |
Distance functions using correlations
|
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation |
Distance functions using correlations
|
de.lmu.ifi.dbs.elki.distance.distancefunction.histogram |
Distance functions for one-dimensional histograms.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski |
Minkowski space Lp norms such as the popular Euclidean and
Manhattan distances.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic |
Distance from probability theory, mostly divergences such as K-L-divergence,
J-divergence, F-divergence, χ²-divergence, etc.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces
|
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries |
Distance functions designed for time series
Note that some regular distance functions (e.g., Euclidean) are also used on
time series.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction |
Similarity functions
|
tutorial.distancefunction |
Classes from the tutorial on implementing distance functions
|
Modifier and Type | Class and Description |
---|---|
class |
BrayCurtisDistanceFunction
Bray-Curtis distance function / Sørensen–Dice coefficient for continuous
vector spaces (not only binary data).
|
class |
MahalanobisDistanceFunction
Mahalanobis quadratic form distance for feature vectors.
|
class |
MatrixWeightedQuadraticDistanceFunction
Matrix weighted quadratic distance, the squared form of
MahalanobisDistanceFunction . |
class |
WeightedCanberraDistanceFunction
Weighted Canberra distance function, a variation of Manhattan distance.
|
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 |
AbsolutePearsonCorrelationDistanceFunction
Absolute Pearson correlation distance function for feature vectors.
|
class |
AbsoluteUncenteredCorrelationDistanceFunction
Absolute uncentered correlation distance function for feature vectors.
|
class |
PearsonCorrelationDistanceFunction
Pearson correlation distance function for feature vectors.
|
class |
SquaredPearsonCorrelationDistanceFunction
Squared Pearson correlation distance function for feature vectors.
|
class |
SquaredUncenteredCorrelationDistanceFunction
Squared uncentered correlation distance function for feature vectors.
|
class |
UncenteredCorrelationDistanceFunction
Uncentered correlation distance.
|
class |
WeightedPearsonCorrelationDistanceFunction
Pearson correlation distance function for feature vectors.
|
class |
WeightedSquaredPearsonCorrelationDistanceFunction
Weighted squared Pearson correlation distance function for feature vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
HistogramMatchDistanceFunction
Distance function based on histogram matching, i.e., Manhattan distance on
the cumulative density function.
|
class |
KolmogorovSmirnovDistanceFunction
Distance function based on the Kolmogorov-Smirnov goodness of fit test.
|
Modifier and Type | Class and Description |
---|---|
class |
MinimumDistanceFunction
Minimum distance for
NumberVector s. |
class |
SquaredEuclideanDistanceFunction
Squared Euclidean distance, optimized for
SparseNumberVector s. |
class |
WeightedSquaredEuclideanDistanceFunction
Weighted squared Euclidean distance for
NumberVector s. |
Modifier and Type | Class and Description |
---|---|
class |
ChiDistanceFunction
χ distance function, symmetric version.
|
class |
ChiSquaredDistanceFunction
χ² distance function, symmetric version.
|
class |
FisherRaoDistanceFunction
Fisher-Rao riemannian metric for (discrete) probability distributions.
|
class |
HellingerDistanceFunction
Hellinger metric / affinity / kernel, Bhattacharyya coefficient, fidelity
similarity, Matusita distance, Hellinger-Kakutani metric on a probability
distribution.
|
class |
JeffreyDivergenceDistanceFunction
Jeffrey Divergence for
NumberVector s is a symmetric, smoothened
version of the KullbackLeiblerDivergenceAsymmetricDistanceFunction . |
class |
JensenShannonDivergenceDistanceFunction
Jensen-Shannon Divergence for
NumberVector s is a symmetric,
smoothened version of the
KullbackLeiblerDivergenceAsymmetricDistanceFunction . |
class |
KullbackLeiblerDivergenceAsymmetricDistanceFunction
Kullback-Leibler divergence, also known as relative entropy,
information deviation, or just KL-distance (albeit asymmetric).
|
class |
KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction
Kullback-Leibler divergence, also known as relative entropy, information
deviation or just KL-distance (albeit asymmetric).
|
class |
SqrtJensenShannonDivergenceDistanceFunction
The square root of Jensen-Shannon divergence is a metric.
|
class |
TriangularDiscriminationDistanceFunction
Triangular Discrimination has relatively tight upper and lower bounds to the
Jensen-Shannon divergence, but is much less expensive.
|
class |
TriangularDistanceFunction
Triangular Distance has relatively tight upper and lower bounds to the
(square root of the) Jensen-Shannon divergence, but is much less expensive.
|
Modifier and Type | Class and Description |
---|---|
class |
OnedimensionalDistanceFunction
Distance function that computes the distance between feature vectors as the
absolute difference of their values in a specified dimension only.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractEditDistanceFunction
Edit Distance for FeatureVectors.
|
class |
DerivativeDTWDistanceFunction
Derivative Dynamic Time Warping distance for numerical vectors.
|
class |
DTWDistanceFunction
Dynamic Time Warping distance (DTW) for numerical vectors.
|
class |
EDRDistanceFunction
Edit Distance on Real Sequence distance for numerical vectors.
|
class |
ERPDistanceFunction
Edit Distance With Real Penalty distance for numerical vectors.
|
class |
LCSSDistanceFunction
Longest Common Subsequence distance for numerical vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
Kulczynski1SimilarityFunction
Kulczynski similarity 1.
|
Modifier and Type | Class and Description |
---|---|
class |
MultiLPNorm
Tutorial example Minowski-distance variation with different exponents for
different dimensions for ELKI.
|
class |
TutorialDistanceFunction
Tutorial distance function example for ELKI.
|
Copyright © 2019 ELKI Development Team. License information.