Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering |
Clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional |
Clustering algorithms for one-dimensional data.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.math.statistics |
Statistical tests and methods.
|
de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions |
Kernel functions from statistics.
|
Modifier and Type | Field and Description |
---|---|
(package private) KernelDensityFunction |
NaiveMeanShiftClustering.kernel
Density estimation kernel.
|
(package private) KernelDensityFunction |
NaiveMeanShiftClustering.Parameterizer.kernel
Kernel function.
|
Constructor and Description |
---|
NaiveMeanShiftClustering(DistanceFunction<? super V> distanceFunction,
KernelDensityFunction kernel,
double range)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
protected KernelDensityFunction |
KNNKernelDensityMinimaClustering.kernel
Kernel density function.
|
protected KernelDensityFunction |
KNNKernelDensityMinimaClustering.Parameterizer.kernel
Kernel density function.
|
Constructor and Description |
---|
KNNKernelDensityMinimaClustering(int dim,
KernelDensityFunction kernel,
KNNKernelDensityMinimaClustering.Mode mode,
int k,
int minwindow)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
private KernelDensityFunction |
LDF.kernel
Kernel density function
|
(package private) KernelDensityFunction |
LDF.Parameterizer.kernel
Kernel density function parameter
|
(package private) KernelDensityFunction |
KDEOS.kernel
Kernel function to use for density estimation.
|
(package private) KernelDensityFunction |
KDEOS.Parameterizer.kernel
Kernel function to use for density estimation.
|
private KernelDensityFunction |
SimpleKernelDensityLOF.kernel
Kernel density function
|
(package private) KernelDensityFunction |
SimpleKernelDensityLOF.Parameterizer.kernel
Kernel density function parameter
|
Constructor and Description |
---|
KDEOS(DistanceFunction<? super O> distanceFunction,
int kmin,
int kmax,
KernelDensityFunction kernel,
double minBandwidth,
double scale,
int idim)
Constructor.
|
LDF(int k,
DistanceFunction<? super O> distance,
KernelDensityFunction kernel,
double h,
double c)
Constructor.
|
SimpleKernelDensityLOF(int k,
DistanceFunction<? super O> distance,
KernelDensityFunction kernel)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
(package private) KernelDensityFunction |
OUTRES.KernelDensityEstimator.kernel
Actual kernel in use
|
Modifier and Type | Method and Description |
---|---|
private void |
KernelDensityEstimator.process(double[] data,
double min,
double max,
KernelDensityFunction kernel,
int window,
double epsilon)
Process a new array
|
Constructor and Description |
---|
KernelDensityEstimator(double[] data,
double min,
double max,
KernelDensityFunction kernel,
int window,
double epsilon)
Initialize and execute kernel density estimation.
|
KernelDensityEstimator(double[] data,
KernelDensityFunction kernel,
double epsilon)
Process an array of data
|
Modifier and Type | Class and Description |
---|---|
class |
BiweightKernelDensityFunction
Biweight (Quartic) kernel density estimator.
|
class |
CosineKernelDensityFunction
Cosine kernel density estimator.
|
class |
EpanechnikovKernelDensityFunction
Epanechnikov kernel density estimator.
|
class |
GaussianKernelDensityFunction
Gaussian kernel density estimator.
|
class |
TriangularKernelDensityFunction
Triangular kernel density estimator.
|
class |
TricubeKernelDensityFunction
Tricube kernel density estimator.
|
class |
TriweightKernelDensityFunction
Triweight kernel density estimator.
|
class |
UniformKernelDensityFunction
Uniform / Rectangular kernel density estimator.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.