A class that represents a univariate conditionally Gaussian distribution.
More...
#include <regression_distribution.hpp>
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| RegressionDistribution () |
| | Default constructor, which creates a Gaussian with zero dimension.
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| mlpack_deprecated | RegressionDistribution (const arma::mat &predictors, const arma::vec &responses) |
| | Create a Conditional Gaussian distribution with conditional mean function obtained by running RegressionFunction on predictors, responses. More...
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| | RegressionDistribution (const arma::mat &predictors, const arma::rowvec &responses) |
| | Create a Conditional Gaussian distribution with conditional mean function obtained by running RegressionFunction on predictors, responses. More...
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template<typename Archive > |
| void | serialize (Archive &ar, const uint32_t) |
| | Serialize the distribution.
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const regression::LinearRegression & | Rf () const |
| | Return regression function.
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regression::LinearRegression & | Rf () |
| | Modify regression function.
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const GaussianDistribution & | Err () const |
| | Return error distribution.
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GaussianDistribution & | Err () |
| | Modify error distribution.
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| void | Train (const arma::mat &observations) |
| | Estimate the Gaussian distribution directly from the given observations. More...
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| mlpack_deprecated void | Train (const arma::mat &observations, const arma::vec &weights) |
| | Estimate parameters using provided observation weights. More...
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| void | Train (const arma::mat &observations, const arma::rowvec &weights) |
| | Estimate parameters using provided observation weights. More...
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| double | Probability (const arma::vec &observation) const |
| | Evaluate probability density function of given observation. More...
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| double | LogProbability (const arma::vec &observation) const |
| | Evaluate log probability density function of given observation. More...
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| mlpack_deprecated void | Predict (const arma::mat &points, arma::vec &predictions) const |
| | Calculate y_i for each data point in points. More...
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| void | Predict (const arma::mat &points, arma::rowvec &predictions) const |
| | Calculate y_i for each data point in points. More...
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const arma::vec & | Parameters () const |
| | Return the parameters (the b vector).
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size_t | Dimensionality () const |
| | Return the dimensionality.
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A class that represents a univariate conditionally Gaussian distribution.
Can be used as an emission distribution with the hmm class to implement HMM regression (HMMR) as described in https://www.ima.umn.edu/preprints/January1994/1195.pdf The hmm observations should have the dependent variable in the first row, with the independent variables in the other rows.
◆ RegressionDistribution() [1/2]
| mlpack_deprecated mlpack::distribution::RegressionDistribution::RegressionDistribution |
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const arma::mat & |
predictors, |
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const arma::vec & |
responses |
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Create a Conditional Gaussian distribution with conditional mean function obtained by running RegressionFunction on predictors, responses.
- Parameters
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| predictors | Matrix of predictors (X). |
| responses | Vector of responses (y). |
◆ RegressionDistribution() [2/2]
| mlpack::distribution::RegressionDistribution::RegressionDistribution |
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const arma::mat & |
predictors, |
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const arma::rowvec & |
responses |
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inline |
Create a Conditional Gaussian distribution with conditional mean function obtained by running RegressionFunction on predictors, responses.
- Parameters
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| predictors | Matrix of predictors (X). |
| responses | Vector of responses (y). |
◆ LogProbability()
| double mlpack::distribution::RegressionDistribution::LogProbability |
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const arma::vec & |
observation | ) |
const |
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Evaluate log probability density function of given observation.
- Parameters
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| observation | Point to evaluate log probability at. |
◆ Predict() [1/2]
| void RegressionDistribution::Predict |
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const arma::mat & |
points, |
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arma::vec & |
predictions |
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Calculate y_i for each data point in points.
- Parameters
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| points | The data points to calculate with. |
| predictions | Y, will contain calculated values on completion. |
◆ Predict() [2/2]
| void RegressionDistribution::Predict |
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const arma::mat & |
points, |
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arma::rowvec & |
predictions |
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Calculate y_i for each data point in points.
- Parameters
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| points | The data points to calculate with. |
| predictions | Y, will contain calculated values on completion. |
◆ Probability()
| double RegressionDistribution::Probability |
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const arma::vec & |
observation | ) |
const |
Evaluate probability density function of given observation.
- Parameters
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| observation | Point to evaluate probability at. |
◆ Train() [1/3]
| void RegressionDistribution::Train |
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const arma::mat & |
observations | ) |
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Estimate the Gaussian distribution directly from the given observations.
Estimate parameters using provided observation weights.
- Parameters
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| observations | List of observations. |
◆ Train() [2/3]
| void RegressionDistribution::Train |
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const arma::mat & |
observations, |
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const arma::vec & |
weights |
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Estimate parameters using provided observation weights.
- Parameters
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| observations | List of observations. |
| weights | Probability that given observation is from distribution. |
| weights | Probability that given observation is from distribution. |
◆ Train() [3/3]
| void RegressionDistribution::Train |
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const arma::mat & |
observations, |
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const arma::rowvec & |
weights |
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Estimate parameters using provided observation weights.
- Parameters
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| observations | List of observations. |
| weights | Probability that given observation is from distribution. |
The documentation for this class was generated from the following files:
