lucid::Tuner Class Reference

Optimise the kernel hyperparameters. More...

#include <Tuner.h>

Inheritance diagram for lucid::Tuner:

Public Member Functions
void	tune (Estimator &estimator, ConstMatrixRef training_inputs, ConstMatrixRef training_outputs) const
	Optimise the kernel hyperparameters.
void	tune_online (Estimator &estimator, ConstMatrixRef training_inputs, const OutputComputer &training_outputs) const
	Optimise the kernel hyperparameters.
virtual std::string	to_string () const
	Obtain the string representation of this object.

Protected Member Functions
virtual void	tune_impl (Estimator &estimator, ConstMatrixRef training_inputs, const OutputComputer &training_outputs) const =0
	Optimise the kernel hyperparameters.

Detailed Description

Optimise the kernel hyperparameters.

Given a kernel, the optimiser finds the best hyperparameters for the kernel. The optimiser subclass determines the optimisation algorithm.

Member Function Documentation

to_string()

std::string lucid::Tuner::to_string ( ) const

nodiscardvirtual

Obtain the string representation of this object.

Returns

string representation of this object

Reimplemented in lucid::GridSearchTuner, lucid::LbfgsTuner, and lucid::MedianHeuristicTuner.

tune()

void lucid::Tuner::tune	(	Estimator &	estimator,
		ConstMatrixRef	training_inputs,
		ConstMatrixRef	training_outputs ) const

Optimise the kernel hyperparameters.

Starting from the initial guess, the optimiser finds the best hyperparameters for the kernel.

Note

The method must call the consolidate method of the estimator to ensure that the kernel is ready to be used.

Precondition

The number of rows in the training inputs should be equal to the number of rows in the training outputs.

Parameters

estimator	estimator to optimise
training_inputs	training input data
training_outputs	training output data

tune_impl()

virtual void lucid::Tuner::tune_impl ( Estimator & estimator, ConstMatrixRef training_inputs, const OutputComputer & training_outputs ) const

protectedpure virtual

Optimise the kernel hyperparameters.

Starting from the initial guess, the optimiser finds the best hyperparameters for the kernel. It is up to the subclass to determine the optimisation algorithm used.

Note

The method must call the consolidate method of the estimator to ensure that the kernel is ready to be used.

Precondition

The number of rows in the training inputs should be equal to the number of rows in the training outputs.

Todo

If the OutputComputer becomes a bottleneck, consider having a separate method for when the outputs are available from the get-go.

Parameters

estimator	estimator to optimise
training_inputs	training input data
training_outputs	training output data. It uses an OutputComputer to compute the outputs when needed

Implemented in lucid::GridSearchTuner, lucid::LbfgsTuner, and lucid::MedianHeuristicTuner.

tune_online()

void lucid::Tuner::tune_online	(	Estimator &	estimator,
		ConstMatrixRef	training_inputs,
		const OutputComputer &	training_outputs ) const

Optimise the kernel hyperparameters.

Starting from the initial guess, the optimiser finds the best hyperparameters for the kernel.

Note

The method must call the consolidate method of the estimator to ensure that the kernel is ready to be used.

Precondition

The number of rows in the training inputs should be equal to the number of rows in the training outputs.

Parameters

estimator	estimator to optimise
training_inputs	training input data
training_outputs	training output data. It uses an OutputComputer to compute the outputs when needed

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

• lucid/model/Tuner.h
• lucid/model/Tuner.cpp