| Modifier and Type | Field and Description |
|---|---|
private PrimitiveDistanceFunction<? super O,D> |
AbstractPrimitiveDistanceBasedAlgorithm.distanceFunction
Holds the instance of the distance function specified by
AbstractDistanceBasedAlgorithm.DISTANCE_FUNCTION_ID. |
protected PrimitiveDistanceFunction<O,D> |
AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer.distanceFunction |
| Modifier and Type | Method and Description |
|---|---|
PrimitiveDistanceFunction<? super O,D> |
AbstractPrimitiveDistanceBasedAlgorithm.getDistanceFunction()
Returns the distanceFunction.
|
| Constructor and Description |
|---|
AbstractPrimitiveDistanceBasedAlgorithm(PrimitiveDistanceFunction<? super O,D> distanceFunction)
Constructor.
|
DependencyDerivator(PrimitiveDistanceFunction<V,D> distanceFunction,
NumberFormat nf,
PCAFilteredRunner<V> pca,
int sampleSize,
boolean randomsample)
Constructor.
|
| Constructor and Description |
|---|
KMeans(PrimitiveDistanceFunction<? super V,D> distanceFunction,
int k,
int maxiter,
Long seed)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected PrimitiveDistanceFunction<O,D> |
AbstractDistanceBasedSpatialOutlier.Parameterizer.distanceFunction
The distance function to use on the non-spatial attributes.
|
| Constructor and Description |
|---|
SLOM(NeighborSetPredicate.Factory<N> npred,
PrimitiveDistanceFunction<O,D> nonSpatialDistanceFunction)
Constructor.
|
SOF(NeighborSetPredicate.Factory<N> npred,
PrimitiveDistanceFunction<O,D> nonSpatialDistanceFunction)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected PrimitiveDistanceFunction<? super O,D> |
PrimitiveDistanceQuery.distanceFunction
The distance function we use.
|
| Modifier and Type | Method and Description |
|---|---|
PrimitiveDistanceFunction<? super O,D> |
PrimitiveDistanceQuery.getDistanceFunction() |
| Constructor and Description |
|---|
PrimitiveDistanceQuery(Relation<? extends O> relation,
PrimitiveDistanceFunction<? super O,D> distanceFunction)
Constructor.
|
PrimitiveDistanceSimilarityQuery(Relation<? extends O> relation,
PrimitiveDistanceFunction<? super O,D> distanceFunction,
PrimitiveSimilarityFunction<? super O,D> similarityFunction)
Constructor.
|
| Modifier and Type | Interface and Description |
|---|---|
interface |
PrimitiveDoubleDistanceFunction<O>
Interface for distance functions that can provide a raw double value.
|
interface |
SpatialPrimitiveDistanceFunction<V extends SpatialComparable,D extends Distance<D>>
API for a spatial primitive distance function.
|
interface |
SpatialPrimitiveDoubleDistanceFunction<V extends SpatialComparable>
Interface combining spatial primitive distance functions with primitive
number distance functions.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractCosineDistanceFunction
Abstract base class for Cosine and ArcCosine distances.
|
class |
AbstractPrimitiveDistanceFunction<O,D extends Distance<D>>
AbstractDistanceFunction provides some methods valid for any extending class.
|
class |
AbstractVectorDoubleDistanceFunction
Abstract base class for the most common family of distance functions: defined
on number vectors and returning double values.
|
class |
ArcCosineDistanceFunction
Cosine distance function for feature vectors.
|
class |
CosineDistanceFunction
Cosine distance function for feature vectors.
|
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 |
SquaredEuclideanDistanceFunction
Provides the squared Euclidean distance for FeatureVectors.
|
class |
WeightedDistanceFunction
Provides the Weighted distance for feature vectors.
|
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 |
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 |
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 |
DimensionsSelectingEuclideanDistanceFunction
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 |
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.
|
| Modifier and Type | Field and Description |
|---|---|
private PrimitiveDistanceFunction<? super V,DoubleDistance> |
WeightedCovarianceMatrixBuilder.weightDistance
Holds the distance function used for weight calculation
|