#include <Mixture.hpp>
◆ Mixture() [1/2]
hops::Mixture::Mixture |
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const std::vector< std::shared_ptr< Model >> & |
models | ) |
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inlineexplicit |
◆ Mixture() [2/2]
hops::Mixture::Mixture |
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std::vector< std::shared_ptr< Model >> |
models, |
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std::vector< double > |
weights |
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) |
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inline |
◆ computeExpectedFisherInformation()
std::optional<MatrixType> hops::Mixture::computeExpectedFisherInformation |
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const VectorType & |
x | ) |
const |
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inlineoverridevirtual |
◆ computeLogLikelihoodGradient()
@ Brief Implementation derived from using chain rule on log(sum(...)).
- Parameters
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- Returns
Reimplemented from hops::Model.
◆ computeNegativeLogLikelihood()
MatrixType::Scalar hops::Mixture::computeNegativeLogLikelihood |
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const VectorType & |
x | ) |
const |
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inlineoverridevirtual |
Evaluates the negative log likelihood for input x.
- Parameters
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- Returns
Implements hops::Model.
The documentation for this class was generated from the following file: