cmp::mean::ModelClusterMean Class Reference

Blended mean function that interpolates local GP means using classifier probabilities. More...

#include <model_cluster.h>

Inheritance diagram for cmp::mean::ModelClusterMean:

Collaboration diagram for cmp::mean::ModelClusterMean:

Public Member Functions
	ModelClusterMean (cmp::ModelCluster *modelCluster, cmp::classifier::Classifier *classifier)
double	eval (const Eigen::VectorXd &x, const Eigen::VectorXd &par) const
double	evalGradient (const Eigen::VectorXd &x, const Eigen::VectorXd &par, const size_t &i) const
double	evalHessian (const Eigen::VectorXd &x, const Eigen::VectorXd &par, const size_t &i, const size_t &j) const
Public Member Functions inherited from cmp::mean::Mean
virtual	~Mean ()=default

Static Public Member Functions
static std::shared_ptr< Mean >	make (cmp::ModelCluster *modelCluster, cmp::classifier::Classifier *classifier)

Private Attributes
cmp::ModelCluster *	pModelCluster_
	Pointer to the underlying model cluster manager.
cmp::classifier::Classifier *	pClassifier_
	Pointer to the classifier used for coordinate probability assignment.

Detailed Description

Blended mean function that interpolates local GP means using classifier probabilities.

Mathematical Formulation The blended mean function at input $x$ is evaluated as:

\[ M(x) = \sum_{k=1}^K P(C=k | x) m_k(x; \theta_k) \]

where $P(C=k | x)$ is the classifier-derived probability that $x$ belongs to cluster $k$, and $m_k$ is the mean function of the $k$-th cluster's GP.

Implementation Algorithm

1. Queries the classifier for the cluster membership probability vector at input $x$.
2. Evaluates the local mean function for each cluster GP at $x$.
3. Returns the dot product of the probability vector and the local GP mean vector.

Constructor & Destructor Documentation

ModelClusterMean()

cmp::mean::ModelClusterMean::ModelClusterMean ( cmp::ModelCluster *  modelCluster, cmp::classifier::Classifier *  classifier  )

inline

Member Function Documentation

eval()

double cmp::mean::ModelClusterMean::eval ( const Eigen::VectorXd &  x, const Eigen::VectorXd &  par  ) const

inlinevirtual

Implements cmp::mean::Mean.

evalGradient()

double cmp::mean::ModelClusterMean::evalGradient ( const Eigen::VectorXd &  x, const Eigen::VectorXd &  par, const size_t &  i  ) const

inlinevirtual

Implements cmp::mean::Mean.

evalHessian()

double cmp::mean::ModelClusterMean::evalHessian ( const Eigen::VectorXd &  x, const Eigen::VectorXd &  par, const size_t &  i, const size_t &  j  ) const

inlinevirtual

Implements cmp::mean::Mean.

make()

static std::shared_ptr< Mean > cmp::mean::ModelClusterMean::make ( cmp::ModelCluster *  modelCluster, cmp::classifier::Classifier *  classifier  )

inlinestatic

Member Data Documentation

pClassifier_

cmp::classifier::Classifier* cmp::mean::ModelClusterMean::pClassifier_

private

Pointer to the classifier used for coordinate probability assignment.

pModelCluster_

cmp::ModelCluster* cmp::mean::ModelClusterMean::pModelCluster_

private

Pointer to the underlying model cluster manager.

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

• include/model_cluster.h