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::Col< size_t > &numObservations) | |
| Define the multidimensional discrete distribution as having numObservations possible observations. More... | |
| DiscreteDistribution (const std::vector< arma::vec > &probabilities) | |
| Define the multidimensional discrete distribution as having the given probabilities for each observation. More... | |
| size_t | Dimensionality () const |
| Get the dimensionality of the distribution. More... | |
| double | LogProbability (const arma::vec &observation) const |
| Return the log probability of the given observation. More... | |
| void | LogProbability (const arma::mat &x, arma::vec &logProbabilities) const |
| Returns the Log probability of the given matrix. More... | |
| arma::vec & | Probabilities (const size_t dim=0) |
| Return the vector of probabilities for the given dimension. More... | |
| const arma::vec & | Probabilities (const size_t dim=0) const |
| Modify the vector of probabilities for the given dimension. More... | |
| double | Probability (const arma::vec &observation) const |
| Return the probability of the given observation. More... | |
| void | Probability (const arma::mat &x, arma::vec &probabilities) const |
| Calculates the Discrete probability density function for each data point (column) in the given matrix. 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... | |
template < typename Archive > | |
| void | serialize (Archive &ar, const uint32_t) |
| Serialize the distribution. More... | |
| void | Train (const arma::mat &observations) |
| Estimate the probability distribution directly from the given observations. More... | |
| void | Train (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... | |
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 45 of file discrete_distribution.hpp.
Constructor & Destructor Documentation
◆ DiscreteDistribution() [1/4]
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inline |
Default constructor, which creates a distribution that has no observations.
Definition at line 52 of file discrete_distribution.hpp.
◆ DiscreteDistribution() [2/4]
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inline |
Define the discrete distribution as having numObservations possible observations.
The probability in each state will be set to (1 / numObservations).
- Parameters
-
numObservations Number of possible observations this distribution can have.
Definition at line 63 of file discrete_distribution.hpp.
◆ DiscreteDistribution() [3/4]
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inline |
Define the multidimensional discrete distribution as having numObservations possible observations.
The probability in each state will be set to (1 / numObservations of each dimension).
- Parameters
-
numObservations Number of possible observations this distribution can have.
Definition at line 76 of file discrete_distribution.hpp.
◆ DiscreteDistribution() [4/4]
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inline |
Define the multidimensional discrete distribution as having the given probabilities for each observation.
- Parameters
-
probabilities Probabilities of each possible observation.
Definition at line 98 of file discrete_distribution.hpp.
Member Function Documentation
◆ Dimensionality()
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inline |
Get the dimensionality of the distribution.
Definition at line 117 of file discrete_distribution.hpp.
◆ LogProbability() [1/2]
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inline |
Return the log 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
-
observation Observation to return the log probability of.
- Returns
- Log probability of the given observation.
Definition at line 166 of file discrete_distribution.hpp.
References DiscreteDistribution::Probability().
◆ LogProbability() [2/2]
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inline |
Returns the Log probability of the given matrix.
These values are stored in logProbabilities.
- Parameters
-
x List of observations. logProbabilities Output log-probabilities for each input observation.
Definition at line 194 of file discrete_distribution.hpp.
References DiscreteDistribution::Probability(), DiscreteDistribution::Random(), and DiscreteDistribution::Train().
◆ Probabilities() [1/2]
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inline |
Return the vector of probabilities for the given dimension.
Definition at line 232 of file discrete_distribution.hpp.
◆ Probabilities() [2/2]
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inline |
Modify the vector of probabilities for the given dimension.
Definition at line 234 of file discrete_distribution.hpp.
◆ Probability() [1/2]
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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
-
observation Observation to return the probability of.
- Returns
- Probability of the given observation.
Definition at line 127 of file discrete_distribution.hpp.
References Log::Fatal.
Referenced by DiscreteDistribution::LogProbability(), and DiscreteDistribution::Probability().
◆ Probability() [2/2]
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inline |
Calculates the Discrete probability density function for each data point (column) in the given matrix.
- Parameters
-
x List of observations. probabilities Output probabilities for each input observation.
Definition at line 179 of file discrete_distribution.hpp.
References DiscreteDistribution::Probability().
◆ Random()
| arma::vec Random | ( | ) | const |
Return a randomly generated observation (one-dimensional vector; one observation) according to the probability distribution defined by this object.
- Returns
- Random observation.
Referenced by DiscreteDistribution::LogProbability(), MockCategoricalData(), and AggregatedPolicy< PolicyType >::Sample().
◆ serialize()
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inline |
Serialize the distribution.
Definition at line 241 of file discrete_distribution.hpp.
◆ Train() [1/2]
| void Train | ( | 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
-
observations List of observations.
Referenced by DiscreteDistribution::LogProbability().
◆ Train() [2/2]
| void Train | ( | 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
-
observations List of observations. probabilities List of probabilities that each observation is actually from this distribution.
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/core/dists/discrete_distribution.hpp