Uses of Class
jsat.distributions.ContinuousDistribution

Packages that use ContinuousDistribution

Package	Description
jsat.classifiers.bayesian
jsat.classifiers.boosting
jsat.distributions
jsat.distributions.empirical
jsat.testing.goodnessoffit
jsat.utils

Uses of ContinuousDistribution in jsat.classifiers.bayesian

Methods in jsat.classifiers.bayesian that return ContinuousDistribution

Modifier and Type	Method and Description
protected abstract ContinuousDistribution	NaiveBayes.NumericalHandeling.fit(Vec y)

Uses of ContinuousDistribution in jsat.classifiers.boosting

Methods in jsat.classifiers.boosting that return ContinuousDistribution

Modifier and Type	Method and Description
ContinuousDistribution	WaggingNormal.getDistribution()
ContinuousDistribution	Wagging.getDistribution() Returns the distribution used for weight sampling

Methods in jsat.classifiers.boosting with parameters of type ContinuousDistribution

Modifier and Type	Method and Description
void	WaggingNormal.setDistribution(ContinuousDistribution dist)
void	Wagging.setDistribution(ContinuousDistribution dist) Sets the distribution to select the random weights from

Constructors in jsat.classifiers.boosting with parameters of type ContinuousDistribution

Constructor and Description
Wagging(ContinuousDistribution dist, Classifier weakL, int iterations) Creates a new Wagging classifier
Wagging(ContinuousDistribution dist, Regressor weakR, int iterations) Creates a new Wagging regressor

Uses of ContinuousDistribution in jsat.distributions

Subclasses of ContinuousDistribution in jsat.distributions

Modifier and Type	Class and Description
class	Beta
class	Cauchy
class	ChiSquared
class	Exponential
class	FisherSendor Also known as the F distribution.
class	Gamma
class	Kolmogorov
class	Laplace
class	Levy Implementation of the Levy ContinuousDistribution
class	Logistic
class	LogNormal
class	LogUniform The Log Uniform distribution is such that if X is the distribution, then Y = log(X) is uniformly distributed.
class	MaxwellBoltzmann
class	Normal
class	Pareto
class	Rayleigh
class	StudentT
class	TruncatedDistribution This distribution truncates a given continuous distribution only be valid for values in the range (min, max].
class	Uniform
class	Weibull

Methods in jsat.distributions that return ContinuousDistribution

Modifier and Type	Method and Description
ContinuousDistribution	Weibull.clone()
ContinuousDistribution	Uniform.clone()
ContinuousDistribution	StudentT.clone()
ContinuousDistribution	Rayleigh.clone()
ContinuousDistribution	Pareto.clone()
ContinuousDistribution	Normal.clone()
ContinuousDistribution	MaxwellBoltzmann.clone()
ContinuousDistribution	LogNormal.clone()
ContinuousDistribution	Logistic.clone()
ContinuousDistribution	Laplace.clone()
ContinuousDistribution	Kolmogorov.clone()
ContinuousDistribution	Gamma.clone()
ContinuousDistribution	FisherSendor.clone()
ContinuousDistribution	Exponential.clone()
abstract ContinuousDistribution	ContinuousDistribution.clone()
ContinuousDistribution	ChiSquared.clone()
ContinuousDistribution	Cauchy.clone()
ContinuousDistribution	Beta.clone()
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v) Searches the distributions that are known for a possible fit, and returns what appears to be the best fit.
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v, ContinuousDistribution... possibleDistributions) Searches the distributions that are given for a possible fit, and returns what appears to be the best fit.
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v, double KDECutOff) Searches the distributions that are known for a possible fit, and returns what appears to be the best fit.
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v, double KDECutOff, ContinuousDistribution... possibleDistributions) Searches the distributions that are given for a possible fit, and returns what appears to be the best fit.

Methods in jsat.distributions with parameters of type ContinuousDistribution

Modifier and Type	Method and Description
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v, ContinuousDistribution... possibleDistributions) Searches the distributions that are given for a possible fit, and returns what appears to be the best fit.
static ContinuousDistribution	DistributionSearch.getBestDistribution(Vec v, double KDECutOff, ContinuousDistribution... possibleDistributions) Searches the distributions that are given for a possible fit, and returns what appears to be the best fit.
static Function	ContinuousDistribution.getFunctionPDF(ContinuousDistribution dist) Wraps the pdf(double) function of the given distribution in a function object for use.

Constructors in jsat.distributions with parameters of type ContinuousDistribution

Constructor and Description
TruncatedDistribution(ContinuousDistribution base, double min, double max)

Uses of ContinuousDistribution in jsat.distributions.empirical

Subclasses of ContinuousDistribution in jsat.distributions.empirical

Modifier and Type	Class and Description
class	KernelDensityEstimator Kernel Density Estimator, KDE, uses the data set itself to approximate the underlying probability distribution using Kernel Functions.

Uses of ContinuousDistribution in jsat.testing.goodnessoffit

Methods in jsat.testing.goodnessoffit with parameters of type ContinuousDistribution

Modifier and Type	Method and Description
protected double	KSTest.dCalc(ContinuousDistribution cd) Calculates the D statistic for comparison against a continous distribution
double	KSTest.testDist(ContinuousDistribution cd) Returns the p-value for the KS Test against the given distribution cd.

Uses of ContinuousDistribution in jsat.utils

Constructors in jsat.utils with parameters of type ContinuousDistribution

Constructor and Description
GridDataGenerator(ContinuousDistribution noiseSource, int... dimensions) Creates a new Grid data generator, that can be queried for new data sets.
GridDataGenerator(ContinuousDistribution noiseSource, Random rand, int... dimensions) Creates a new Grid data generator, that can be queried for new data sets.