Uses of Interface
elki.utilities.datastructures.arraylike.NumberArrayAdapter
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Packages that use NumberArrayAdapter Package Description elki.data Basic classes for different data types, database object types and label types.elki.data.projection Data projections.elki.data.uncertain.uncertainifier Classes to generate uncertain objects from existing certain data.elki.math.statistics Statistical tests and methods.elki.math.statistics.dependence Statistical measures of dependence, such as correlation.elki.math.statistics.dependence.mcde Tests tailored to be used withMCDEDependence
.elki.math.statistics.distribution.estimator Estimators for statistical distributions.elki.math.statistics.distribution.estimator.meta Meta estimators: estimators that do not actually estimate themselves, but instead use other estimators, e.g., on a trimmed data set, or as an ensemble.elki.math.statistics.intrinsicdimensionality Methods for estimating the intrinsic dimensionality.elki.utilities.datastructures.arraylike Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.elki.utilities.scaling.outlier Scaling of outlier scores, that require a statistical analysis of the occurring values. -
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Uses of NumberArrayAdapter in elki.data
Methods in elki.data with parameters of type NumberArrayAdapter Modifier and Type Method Description <A> BitVector
BitVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> ByteVector
ByteVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> DoubleVector
DoubleVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> FloatVector
FloatVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> IntegerVector
IntegerVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> V
NumberVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
Instantiate from any number-array like object.<A> OneDimensionalDoubleVector
OneDimensionalDoubleVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> ShortVector
ShortVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> SparseByteVector
SparseByteVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> SparseDoubleVector
SparseDoubleVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> SparseFloatVector
SparseFloatVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> SparseIntegerVector
SparseIntegerVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
<A> SparseShortVector
SparseShortVector.Factory. newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
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Uses of NumberArrayAdapter in elki.data.projection
Classes in elki.data.projection that implement NumberArrayAdapter Modifier and Type Class Description private class
FeatureSelection.ProjectedNumberFeatureVectorAdapter
Adapter for generating number vectors without reboxing. -
Uses of NumberArrayAdapter in elki.data.uncertain.uncertainifier
Methods in elki.data.uncertain.uncertainifier with parameters of type NumberArrayAdapter Modifier and Type Method Description <A> SimpleGaussianContinuousUncertainObject
SimpleGaussianUncertainifier. newFeatureVector(java.util.Random rand, A array, NumberArrayAdapter<?,A> adapter)
<A> UO
Uncertainifier. newFeatureVector(java.util.Random rand, A array, NumberArrayAdapter<?,A> adapter)
Generate a new uncertain object.<A> UniformContinuousUncertainObject
UniformUncertainifier. newFeatureVector(java.util.Random rand, A array, NumberArrayAdapter<?,A> adapter)
<A> UnweightedDiscreteUncertainObject
UnweightedDiscreteUncertainifier. newFeatureVector(java.util.Random rand, A array, NumberArrayAdapter<?,A> adapter)
<A> WeightedDiscreteUncertainObject
WeightedDiscreteUncertainifier. newFeatureVector(java.util.Random rand, A array, NumberArrayAdapter<?,A> adapter)
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Uses of NumberArrayAdapter in elki.math.statistics
Methods in elki.math.statistics with parameters of type NumberArrayAdapter Modifier and Type Method Description static <A> double[]
ProbabilityWeightedMoments. alphaBetaPWM(A data, NumberArrayAdapter<?,A> adapter, int nmom)
Compute the alpha_r and beta_r factors in parallel using the method of probability-weighted moments.static <A> double[]
ProbabilityWeightedMoments. alphaPWM(A data, NumberArrayAdapter<?,A> adapter, int nmom)
Compute the alpha_r factors using the method of probability-weighted moments.static <A> double[]
ProbabilityWeightedMoments. betaPWM(A data, NumberArrayAdapter<?,A> adapter, int nmom)
Compute the beta_r factors using the method of probability-weighted moments.static <A> double[]
ProbabilityWeightedMoments. samLMR(A sorted, NumberArrayAdapter<?,A> adapter, int nmom)
Compute the sample L-Moments using probability weighted moments. -
Uses of NumberArrayAdapter in elki.math.statistics.dependence
Methods in elki.math.statistics.dependence with parameters of type NumberArrayAdapter Modifier and Type Method Description private <A> java.util.ArrayList<int[]>
MaximumConditionalEntropy. buildPartitions(NumberArrayAdapter<?,A> adapter1, A data1, int len, int depth)
Partitions an attribute.protected static <A,B>
double[]HoeffdingsD. computeBivariateRanks(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2, int len)
Compute bivariate ranks.protected static <A> double[]
DCor. computeDistances(NumberArrayAdapter<?,A> adapter, A data)
Compute the double-centered delta matrix.static <A> double[]
Dependence.Utils. computeNormalizedRanks(NumberArrayAdapter<?,A> adapter, A data, int len)
Compute ranks of all objects, normalized to [0;1] (where 0 is the smallest value, 1 is the largest).<A,B>
doubleDCor. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A> double[]
DCor. dependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)
default <A> double
Dependence. dependence(NumberArrayAdapter<?,A> adapter, A data1, A data2)
Measure the dependence of two variables.<A,B>
doubleDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
Measure the dependence of two variables.default <A> double[]
Dependence. dependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)
Measure the dependence of two variables.<A,B>
doubleHiCSDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleHoeffdingsD. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleHoughSpaceMeasure. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleJensenShannonEquiwidthDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleMaximumConditionalEntropy. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleMCDEDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A> double[]
MCDEDependence. dependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)
<A,B>
doubleMutualInformationEquiwidthDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doublePearsonCorrelationDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A> double[]
PearsonCorrelationDependence. dependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)
<A,B>
doubleSlopeDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleSlopeInversionDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleSpearmanCorrelationDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A,B>
doubleSURFINGDependence. dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
<A> double
MCDEDependence. higherOrderDependence(NumberArrayAdapter<?,A> adapter, java.util.List<? extends A> data)
Runs MCDE Algorithm with possibly more than two dimensionsstatic <A> double[]
Dependence.Utils. ranks(NumberArrayAdapter<?,A> adapter, A data, int len)
Compute ranks of all objects, ranging from 1 to len.static <A> double[]
Dependence.Utils. ranks(NumberArrayAdapter<?,A> adapter, A data, int[] idx)
Compute ranks of all objects, ranging from 1 to len.static <A,B>
intDependence.Utils. size(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2)
Validate the length of the two data sets (must be the same, and non-zero)static <A> int
Dependence.Utils. size(NumberArrayAdapter<?,A> adapter, java.util.Collection<? extends A> data)
Validate the length of the two data sets (must be the same, and non-zero)static <A> int[]
Dependence.Utils. sortedIndex(NumberArrayAdapter<?,A> adapter, A data, int len)
Build a sorted index of objects. -
Uses of NumberArrayAdapter in elki.math.statistics.dependence.mcde
Methods in elki.math.statistics.dependence.mcde with parameters of type NumberArrayAdapter Modifier and Type Method Description <A> R
MCDETest. correctedRanks(NumberArrayAdapter<?,A> adapter, A data, int len)
Compute the corrected rank index.<A> MWPTest.MWPRanking
MWPTest. correctedRanks(NumberArrayAdapter<?,A> adapter, A data, int len)
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Uses of NumberArrayAdapter in elki.math.statistics.distribution.estimator
Methods in elki.math.statistics.distribution.estimator with parameters of type NumberArrayAdapter Modifier and Type Method Description <A> D
DistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
General form of the parameter estimation<A> ExpGammaDistribution
ExpGammaExpMOMEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> GammaDistribution
GammaChoiWetteEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> InverseGaussianDistribution
InverseGaussianMLEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> LaplaceDistribution
LaplaceMLEEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
LMMDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
LogMADDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
LogMeanVarianceEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
LogMOMDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> LogNormalDistribution
LogNormalLevenbergMarquardtKDEEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
MADDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
MeanVarianceDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
default <A> D
MOMDistributionEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> NormalDistribution
NormalLevenbergMarquardtKDEEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> RayleighDistribution
RayleighMLEEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> UniformDistribution
UniformEnhancedMinMaxEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> UniformDistribution
UniformMinMaxEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
static <A> double
LogMOMDistributionEstimator. min(A data, NumberArrayAdapter<?,A> adapter, double minmin, double margin)
Utility function to find minimum and maximum values. -
Uses of NumberArrayAdapter in elki.math.statistics.distribution.estimator.meta
Methods in elki.math.statistics.distribution.estimator.meta with parameters of type NumberArrayAdapter Modifier and Type Method Description <A> Distribution
BestFitEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> D
TrimmedEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
<A> D
WinsorizingEstimator. estimate(A data, NumberArrayAdapter<?,A> adapter)
static <A> double[]
TrimmedEstimator. toPrimitiveDoubleArray(A data, NumberArrayAdapter<?,A> adapter)
Local copy, see ArrayLikeUtil.toPrimitiveDoubleArray. -
Uses of NumberArrayAdapter in elki.math.statistics.intrinsicdimensionality
Fields in elki.math.statistics.intrinsicdimensionality declared as NumberArrayAdapter Modifier and Type Field Description private NumberArrayAdapter<?,? super A>
LMomentsEstimator.ReverseAdapter. inner
Adapter class.Methods in elki.math.statistics.intrinsicdimensionality with parameters of type NumberArrayAdapter Modifier and Type Method Description static <A> int
DistanceBasedIntrinsicDimensionalityEstimator. countLeadingZeros(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
AggregatedHillEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
default <A> double
DistanceBasedIntrinsicDimensionalityEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter)
Estimate from a distance list.<A> double
DistanceBasedIntrinsicDimensionalityEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int size)
Estimate from a distance list.<A> double
EnsembleEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
GEDEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
HillEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
LMomentsEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
MOMEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
PWM2Estimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
PWMEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
RABIDEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int size)
<A> double
RVEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
<A> double
ZipfEstimator. estimate(A data, NumberArrayAdapter<?,? super A> adapter, int end)
Constructors in elki.math.statistics.intrinsicdimensionality with parameters of type NumberArrayAdapter Constructor Description ReverseAdapter(NumberArrayAdapter<?,? super A> inner, int begin, int end)
Constructor. -
Uses of NumberArrayAdapter in elki.utilities.datastructures.arraylike
Classes in elki.utilities.datastructures.arraylike that implement NumberArrayAdapter Modifier and Type Class Description class
DoubleArray
Array of double values (primitive, avoiding the boxing overhead of ArrayList). class
DoubleArrayAdapter
Use adouble[]
in the ArrayAdapter API.class
FloatArrayAdapter
Use afloat[]
in the ArrayAdapter API.class
IntegerArray
Array of int values (primitive, avoiding the boxing overhead of ArrayList). class
NumberVectorAdapter
Adapter to use a feature vector as an array of features.Fields in elki.utilities.datastructures.arraylike declared as NumberArrayAdapter Modifier and Type Field Description static NumberArrayAdapter<java.lang.Double,double[]>
ArrayLikeUtil. DOUBLEARRAYADAPTER
Use a double array in the array API.static NumberArrayAdapter<java.lang.Float,float[]>
ArrayLikeUtil. FLOATARRAYADAPTER
Use a float array in the array API.Methods in elki.utilities.datastructures.arraylike with parameters of type NumberArrayAdapter Modifier and Type Method Description static <A> int
ArrayLikeUtil. getIndexOfMaximum(A array, NumberArrayAdapter<?,A> adapter)
Returns the index of the maximum of the given values.static <A> double[]
ArrayLikeUtil. toPrimitiveDoubleArray(A array, NumberArrayAdapter<?,? super A> adapter)
Convert a numeric array-like to adouble[]
.static <A> float[]
ArrayLikeUtil. toPrimitiveFloatArray(A array, NumberArrayAdapter<?,? super A> adapter)
Convert a numeric array-like to afloat[]
.static <A> int[]
ArrayLikeUtil. toPrimitiveIntegerArray(A array, NumberArrayAdapter<?,? super A> adapter)
Convert a numeric array-like to aint[]
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Uses of NumberArrayAdapter in elki.utilities.scaling.outlier
Methods in elki.utilities.scaling.outlier with parameters of type NumberArrayAdapter Modifier and Type Method Description private <A> double[]
SigmoidOutlierScaling. MStepLevenbergMarquardt(double a, double b, long[] t, A array, NumberArrayAdapter<?,A> adapter)
M-Step using a modified Levenberg-Marquardt method.<A> void
COPOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
HeDESNormalizationOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
LogRankingPseudoOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
MixtureModelOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
MultiplicativeInverseScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
OutlierGammaScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
OutlierLinearScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
OutlierMinusLogScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
OutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
Prepare is called once for each data set, before getScaled() will be called.<A> void
OutlierSqrtScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
RankingPseudoOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
SigmoidOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
SqrtStandardDeviationScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
StandardDeviationScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
<A> void
TopKOutlierScaling. prepare(A array, NumberArrayAdapter<?,A> adapter)
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