Implementation of the Normal Distribution function. More...
Public Member Functions | |
| NormalDistribution () | |
| Default constructor, which creates a Normal distribution with zero dimension. More... | |
| NormalDistribution (const DataType &mean, const DataType &sigma) | |
| Create a Normal distribution with the given mean and sigma. More... | |
| size_t | Dimensionality () const |
| Return the dimensionality of this distribution. More... | |
| DataType | LogProbability (const DataType &observation) const |
| Return the log probabilities of the given matrix of observations. More... | |
| void | LogProbability (const DataType &x, DataType &probabilities) const |
| Calculates the log of normal probability density function for each data point (column) in the given matrix. More... | |
| const DataType & | Mean () const |
| Get the mean. More... | |
| DataType & | Mean () |
| Modify the mean. More... | |
| DataType | Probability (const DataType &observation) const |
| Return the probabilities of the given matrix of observations. More... | |
| void | Probability (const DataType &x, DataType &probabilities) const |
| Calculates the normal probability density function for each data point (column) in the given matrix. More... | |
| void | ProbBackward (const DataType &observation, DataType &dmu, DataType &dsigma) const |
| Stores the gradient of the probabilities of the observations with respect to mean and standard deviation. More... | |
| DataType | Sample () const |
| Return a randomly generated 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... | |
| const DataType & | StandardDeviation () const |
| Get the standard deviation. More... | |
| DataType & | StandardDeviation () |
| Modify the standard deviation. More... | |
Detailed Description
template<typenameDataType=arma::mat>
class mlpack::ann::NormalDistribution< DataType >
Implementation of the Normal Distribution function.
Normal distribution is a function which accepts a mean and a standard deviation term and creates a probability distribution out of it.
- Template Parameters
-
DataType Type of the input data. (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
Definition at line 32 of file normal_distribution.hpp.
Constructor & Destructor Documentation
◆ NormalDistribution() [1/2]
Default constructor, which creates a Normal distribution with zero dimension.
◆ NormalDistribution() [2/2]
| NormalDistribution | ( | const DataType & | mean, |
| const DataType & | sigma | ||
| ) |
Create a Normal distribution with the given mean and sigma.
- Parameters
-
mean The mean of the normal distribution. sigma The standard deviation of the normal distribution.
Member Function Documentation
◆ Dimensionality()
|
inline |
Return the dimensionality of this distribution.
Definition at line 123 of file normal_distribution.hpp.
References NormalDistribution< DataType >::serialize().
◆ LogProbability() [1/2]
| DataType LogProbability | ( | const DataType & | observation | ) | const |
Return the log probabilities of the given matrix of observations.
- Parameters
-
observation The observation matrix.
Referenced by NormalDistribution< DataType >::LogProbability(), and NormalDistribution< DataType >::Probability().
◆ LogProbability() [2/2]
|
inline |
Calculates the log of normal probability density function for each data point (column) in the given matrix.
- Parameters
-
x The observation matrix. probabilities Output log probabilities for each input observation.
Definition at line 97 of file normal_distribution.hpp.
References NormalDistribution< DataType >::LogProbability(), and NormalDistribution< DataType >::Sample().
◆ Mean() [1/2]
|
inline |
Get the mean.
Definition at line 111 of file normal_distribution.hpp.
◆ Mean() [2/2]
|
inline |
Modify the mean.
Definition at line 114 of file normal_distribution.hpp.
◆ Probability() [1/2]
|
inline |
Return the probabilities of the given matrix of observations.
- Parameters
-
observation The observation matrix.
Definition at line 54 of file normal_distribution.hpp.
References NormalDistribution< DataType >::LogProbability(), and NormalDistribution< DataType >::ProbBackward().
Referenced by NormalDistribution< DataType >::Probability().
◆ Probability() [2/2]
|
inline |
Calculates the normal probability density function for each data point (column) in the given matrix.
- Parameters
-
x The observation matrix. probabilities Output probabilities for each input observation.
Definition at line 85 of file normal_distribution.hpp.
References NormalDistribution< DataType >::Probability().
◆ ProbBackward()
| void ProbBackward | ( | const DataType & | observation, |
| DataType & | dmu, | ||
| DataType & | dsigma | ||
| ) | const |
Stores the gradient of the probabilities of the observations with respect to mean and standard deviation.
- Parameters
-
observation The observation matrix. dmu The gradient with respect to mean. dsigma The gradient with respect to the standard deviation.
Referenced by NormalDistribution< DataType >::Probability().
◆ Sample()
| DataType Sample | ( | ) | const |
Return a randomly generated observation according to the probability distribution defined by this object.
- Returns
- Random observation from this Normal distribution.
Referenced by NormalDistribution< DataType >::LogProbability().
◆ serialize()
| void serialize | ( | Archive & | ar, |
| const uint32_t | |||
| ) |
Serialize the distribution.
Referenced by NormalDistribution< DataType >::Dimensionality().
◆ StandardDeviation() [1/2]
|
inline |
Get the standard deviation.
Definition at line 117 of file normal_distribution.hpp.
◆ StandardDeviation() [2/2]
|
inline |
Modify the standard deviation.
Definition at line 120 of file normal_distribution.hpp.
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/dists/normal_distribution.hpp