See: Description
| Interface | Description |
|---|---|
| DiscreteDistribution |
A
DiscreteDistribution provides a probability
distribution over long integer outcomes. |
| Model<E> |
A
Model represents a generic interface for
classes that estimate probabilities of objects. |
| Class | Description |
|---|---|
| AbstractDiscreteDistribution |
An
AbstractDiscreteDistribution provides a default
abstract implementation of discrete distributions. |
| AnnealingSchedule |
An
AnnealingSchedule instance implements a method to
return the learning rate for a specified epoch. |
| BernoulliConstant |
A
BernoulliConstant implements a Bernoulli
distribution with a constant probability of success. |
| BernoulliDistribution |
A
BernoulliDistribution is a multivariate distribution
with two outcomes, 0 (labeled "failure") and 1 (labeled "success"). |
| BernoulliEstimator |
A
BernoulliEstimator provides a maximum likelihood
estimate of a Bernoulli distribution. |
| BinomialDistribution |
A
BinomialDistribution is a discrete distribution over
the number of successes given a fixed number of Bernoulli trials. |
| LogisticRegression |
A
LogisticRegression instance is a multi-class vector
classifier model generating conditional probability estimates of
categories. |
| MultinomialDistribution |
A
MultinomialDistribution results from drawing a fixed
number of samples from a multivariate distribution. |
| MultivariateConstant |
A
MultivariateConstant provides a multinomial
distribution with constant probabilities and labels. |
| MultivariateDistribution |
A
MultivariateDistribution implements a discrete
distribution over a finite set of outcomes numbered consecutively
from zero. |
| MultivariateEstimator |
A
MultivariateEstimator provides a maximum likelihood
estimator of a multivariate distribution based on training samples. |
| OnlineNormalEstimator |
An
OnlineNormalEstimator provides an object that estimates
means, variances, and standard deviations for a stream of numbers
presented one at a time. |
| PoissonConstant |
A
PoissonConstant implements a Poisson
distribution with a fixed mean. |
| PoissonDistribution |
The
PoissonDistribution abstract class is used for
calculating Poisson distributions. |
| PoissonEstimator |
A
PoissonEstimator implements the maximum likelihood
Poisson distribution given training events. |
| PotentialScaleReduction |
The
PotentialScaleReduction class provides an online
computationa of Rhat, the potential scale reduction statistic for
measuring mixing and convergence of multiple Markov chain Monte
Carlo (MCMC) samplers. |
| RegressionPrior |
A
RegressionPrior instance represents a prior
distribution on parameters for linear or logistic regression. |
| Statistics |
The
Statistics class provides static utility methods
for statistical computations. |
| ZipfDistribution |
The
ZipfDistribution class provides a finite
distribution parameterized by a positive integer number of outcomes
with outcome probability inversely proportional to the rank of
the outcome (ordered by probablity). |
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