MLPACK  1.0.7
Public Member Functions | Private Attributes | List of all members
mlpack::distribution::DiscreteDistribution Class Reference

A discrete distribution where the only observations are discrete observations. More...

Public Member Functions

 DiscreteDistribution ()
 Default constructor, which creates a distribution that has no observations. More...
 
 DiscreteDistribution (const size_t numObservations)
 Define the discrete distribution as having numObservations possible observations. More...
 
 DiscreteDistribution (const arma::vec &probabilities)
 Define the discrete distribution as having the given probabilities for each observation. More...
 
size_t Dimensionality () const
 Get the dimensionality of the distribution. More...
 
void Estimate (const arma::mat &observations)
 Estimate the probability distribution directly from the given observations. More...
 
void Estimate (const arma::mat &observations, const arma::vec &probabilities)
 Estimate the probability distribution from the given observations, taking into account the probability of each observation actually being from this distribution. More...
 
const arma::vec & Probabilities () const
 Return the vector of probabilities. More...
 
arma::vec & Probabilities ()
 Modify the vector of probabilities. More...
 
double Probability (const arma::vec &observation) const
 Return the probability of the given observation. More...
 
arma::vec Random () const
 Return a randomly generated observation (one-dimensional vector; one observation) according to the probability distribution defined by this object. More...
 
std::string ToString () const
 

Private Attributes

arma::vec probabilities
 

Detailed Description

A discrete distribution where the only observations are discrete observations.

This is useful (for example) with discrete Hidden Markov Models, where observations are non-negative integers representing specific emissions.

No bounds checking is performed for observations, so if an invalid observation is passed (i.e. observation > numObservations), a crash will probably occur.

This distribution only supports one-dimensional observations, so when passing an arma::vec as an observation, it should only have one dimension (vec.n_rows == 1). Any additional dimensions will simply be ignored.

Note
This class, like every other class in MLPACK, uses arma::vec to represent observations. While a discrete distribution only has positive integers (size_t) as observations, these can be converted to doubles (which is what arma::vec holds). This distribution internally converts those doubles back into size_t before comparisons.

Definition at line 53 of file discrete_distribution.hpp.

Constructor & Destructor Documentation

mlpack::distribution::DiscreteDistribution::DiscreteDistribution ( )
inline

Default constructor, which creates a distribution that has no observations.

Definition at line 59 of file discrete_distribution.hpp.

mlpack::distribution::DiscreteDistribution::DiscreteDistribution ( const size_t  numObservations)
inline

Define the discrete distribution as having numObservations possible observations.

The probability in each state will be set to (1 / numObservations).

Parameters
numObservationsNumber of possible observations this distribution can have.

Definition at line 69 of file discrete_distribution.hpp.

mlpack::distribution::DiscreteDistribution::DiscreteDistribution ( const arma::vec &  probabilities)
inline

Define the discrete distribution as having the given probabilities for each observation.

Parameters
probabilitiesProbabilities of each possible observation.

Definition at line 79 of file discrete_distribution.hpp.

Member Function Documentation

size_t mlpack::distribution::DiscreteDistribution::Dimensionality ( ) const
inline

Get the dimensionality of the distribution.

Definition at line 95 of file discrete_distribution.hpp.

void mlpack::distribution::DiscreteDistribution::Estimate ( const arma::mat &  observations)

Estimate the probability distribution directly from the given observations.

If any of the observations is greater than numObservations, a crash is likely to occur.

Parameters
observationsList of observations.
void mlpack::distribution::DiscreteDistribution::Estimate ( const arma::mat &  observations,
const arma::vec &  probabilities 
)

Estimate the probability distribution from the given observations, taking into account the probability of each observation actually being from this distribution.

Parameters
observationsList of observations.
probabilitiesList of probabilities that each observation is actually from this distribution.
const arma::vec& mlpack::distribution::DiscreteDistribution::Probabilities ( ) const
inline

Return the vector of probabilities.

Definition at line 153 of file discrete_distribution.hpp.

References probabilities.

arma::vec& mlpack::distribution::DiscreteDistribution::Probabilities ( )
inline

Modify the vector of probabilities.

Definition at line 155 of file discrete_distribution.hpp.

References probabilities.

double mlpack::distribution::DiscreteDistribution::Probability ( const arma::vec &  observation) const
inline

Return the probability of the given observation.

If the observation is greater than the number of possible observations, then a crash will probably occur – bounds checking is not performed.

Parameters
observationObservation to return the probability of.
Returns
Probability of the given observation.

Definition at line 105 of file discrete_distribution.hpp.

References mlpack::Log::Debug, and probabilities.

arma::vec mlpack::distribution::DiscreteDistribution::Random ( ) const

Return a randomly generated observation (one-dimensional vector; one observation) according to the probability distribution defined by this object.

Returns
Random observation.
std::string mlpack::distribution::DiscreteDistribution::ToString ( ) const

Member Data Documentation

arma::vec mlpack::distribution::DiscreteDistribution::probabilities
private

Definition at line 163 of file discrete_distribution.hpp.

Referenced by Probabilities(), and Probability().


The documentation for this class was generated from the following file: