# Package weka.estimators

- Interface Summary
  Interface | Description
  --- | ---
  ConditionalEstimator | Interface for conditional probability estimators.
  IncrementalEstimator | Interface for an incremental probability estimators.
  MultivariateEstimator | Interface to Multivariate Distribution Estimation
  UnivariateDensityEstimator | Interface that can be implemented by simple weighted univariate density estimators.
  UnivariateIntervalEstimator | Interface that can be implemented by simple weighted univariate interval estimators.
  UnivariateQuantileEstimator | Interface that can be implemented by simple weighted univariate quantile estimators.

- Class Summary
  Class | Description
  --- | ---
  CheckEstimator | Class for examining the capabilities and finding problems with estimators.
  CheckEstimator.AttrTypes | class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
  CheckEstimator.EstTypes | public class that contains info about the chosen attribute type estimator work on one attribute only
  DDConditionalEstimator | Conditional probability estimator for a discrete domain conditional upon a discrete domain.
  DiscreteEstimator | Simple symbolic probability estimator based on symbol counts.
  DKConditionalEstimator | Conditional probability estimator for a discrete domain conditional upon a numeric domain.
  DNConditionalEstimator | Conditional probability estimator for a discrete domain conditional upon a numeric domain.
  Estimator | Abstract class for all estimators.
  EstimatorUtils | Contains static utility functions for Estimators.
  KDConditionalEstimator | Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
  KernelEstimator | Simple kernel density estimator.
  KKConditionalEstimator | Conditional probability estimator for a numeric domain conditional upon a numeric domain.
  MahalanobisEstimator | Simple probability estimator that places a single normal distribution over the observed values.
  MultivariateGaussianEstimator | Implementation of maximum likelihood Multivariate Distribution Estimation using Normal Distribution.
  NDConditionalEstimator | Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate normal estimators for each discrete conditioning value).
  NNConditionalEstimator | Conditional probability estimator for a numeric domain conditional upon a numeric domain (using Mahalanobis distance).
  NormalEstimator | Simple probability estimator that places a single normal distribution over the observed values.
  PoissonEstimator | Simple probability estimator that places a single Poisson distribution over the observed values.
  UnivariateEqualFrequencyHistogramEstimator | Simple histogram density estimator.
  UnivariateKernelEstimator | Simple weighted kernel density estimator.
  UnivariateMixtureEstimator | Simple weighted mixture density estimator.
  UnivariateNormalEstimator | Simple weighted normal density estimator.