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See:
Description
| Interface Summary | |
|---|---|
| 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 Summary | |
|---|---|
| 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). |
Classes for handling basic statical distributions and estimators.
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