详细描述

The class wraps the Shogun's C-style LBFGS minimizer.

类 LBFGSMinimizer 继承关系图:

Public 成员函数
	LBFGSMinimizer ()

	LBFGSMinimizer (FirstOrderCostFunction *fun)

virtual	~LBFGSMinimizer ()

virtual float64_t	minimize ()

virtual bool	supports_batch_update () const

virtual void	set_lbfgs_parameters (int m=100, int max_linesearch=1000, ELBFGSLineSearch linesearch=BACKTRACKING_STRONG_WOLFE, int max_iterations=1000, float64_t delta=0.0, int past=0, float64_t epsilon=1e-5, float64_t min_step=1e-20, float64_t max_step=1e+20, float64_t ftol=1e-4, float64_t wolfe=0.9, float64_t gtol=0.9, float64_t xtol=1e-16, float64_t orthantwise_c=0.0, int orthantwise_start=0, int orthantwise_end=1)

virtual CMinimizerContext *	save_to_context ()

virtual void	load_from_context (CMinimizerContext *context)

virtual void	set_cost_function (FirstOrderCostFunction *fun)

virtual void	set_penalty_weight (float64_t penalty_weight)

virtual void	set_penalty_type (Penalty *penalty_type)

Protected 成员函数
virtual void	init_minimization ()

virtual void	update_context (CMinimizerContext *context)

virtual float64_t	get_penalty (SGVector< float64_t > var)

virtual void	update_gradient (SGVector< float64_t > gradient, SGVector< float64_t > var)

Protected 属性
int	m_m

int	m_max_linesearch

int	m_linesearch

int	m_max_iterations

float64_t	m_delta

int	m_past

float64_t	m_epsilon

float64_t	m_min_step

float64_t	m_max_step

float64_t	m_ftol

float64_t	m_wolfe

float64_t	m_gtol

float64_t	m_xtol

float64_t	m_orthantwise_c

int	m_orthantwise_start

int	m_orthantwise_end

SGVector< float64_t >	m_target_variable

FirstOrderCostFunction *	m_fun

Penalty *	m_penalty_type

float64_t	m_penalty_weight

构造及析构函数说明

LBFGSMinimizer ( )

在文件 LBFGSMinimizer.cpp 第 37 行定义.

LBFGSMinimizer ( FirstOrderCostFunction * fun )

Constructor

参数

fun	cost function (user have to manully delete the pointer)

在文件 LBFGSMinimizer.cpp 第 47 行定义.

~LBFGSMinimizer ( )

virtual

在文件 LBFGSMinimizer.cpp 第 43 行定义.

成员函数说明

virtual float64_t get_penalty ( SGVector< float64_t > var )

protectedvirtualinherited

Get the penalty given target variables For L2 penalty, the target variable is \(w\) and the value of penalty is \(\lambda \frac{w^t w}{2}\), where \(\lambda\) is the weight of penalty

参数

var	the variable used in regularization

在文件 FirstOrderMinimizer.h 第 164 行定义.

void init_minimization ( )

protectedvirtual

Init before minimization

在文件 LBFGSMinimizer.cpp 第 94 行定义.

virtual void load_from_context ( CMinimizerContext * context )

virtual

Load the given context object to restores mutable variables Usually it is used in deserialization.

参数

context a context object

重载 FirstOrderMinimizer .

在文件 LBFGSMinimizer.h 第 142 行定义.

float64_t minimize ( )

virtual

Do minimization and get the optimal value

返回: optimal value

实现了 FirstOrderMinimizer.

在文件 LBFGSMinimizer.cpp 第 101 行定义.

virtual CMinimizerContext* save_to_context ( )

virtual

Return a context object which stores mutable variables Usually it is used in serialization.

返回: a context object

重载 FirstOrderMinimizer .

在文件 LBFGSMinimizer.h 第 135 行定义.

virtual void set_cost_function ( FirstOrderCostFunction * fun )

virtualinherited

Set cost function used in the minimizer

参数

fun	the cost function

在文件 FirstOrderMinimizer.h 第 92 行定义.

void set_lbfgs_parameters	(	int	m = `100`,
		int	max_linesearch = `1000`,
		ELBFGSLineSearch	linesearch = `BACKTRACKING_STRONG_WOLFE`,
		int	max_iterations = `1000`,
		float64_t	delta = `0.0`,
		int	past = `0`,
		float64_t	epsilon = `1e-5`,
		float64_t	min_step = `1e-20`,
		float64_t	max_step = `1e+20`,
		float64_t	ftol = `1e-4`,
		float64_t	wolfe = `0.9`,
		float64_t	gtol = `0.9`,
		float64_t	xtol = `1e-16`,
		float64_t	orthantwise_c = `0.0`,
		int	orthantwise_start = `0`,
		int	orthantwise_end = `1`
	)

virtual

set L-BFGS parameters For details please see shogun/optimization/lbfgs/lbfgs.h

参数

m	The number of corrections to approximate the inverse hessian matrix. Default value is 100.
max_linesearch	The maximum number of trials to do line search for each L-BFGS update. Default value is 1000.
linesearch	The line search algorithm. Default value is using the backtracking with the strong Wolfe condition line search
max_iterations	The maximum number of iterations for L-BFGS update. Default value is 1000.
delta	Delta for convergence test based on the change of function value. Default value is 0.
past	Distance for delta-based convergence test. Default value is 0.
epsilon	Epsilon for convergence test based on the change of gradient. Default value is 1e-5
min_step	The minimum step of the line search. The default value is 1e-20
max_step	The maximum step of the line search. The default value is 1e+20
ftol	A parameter used in Armijo condition. Default value is 1e-4
wolfe	A parameter used in curvature condition. Default value is 0.9
gtol	A parameter used in Morethuente linesearch to control the accuracy. Default value is 0.9
xtol	The machine precision for floating-point values. Default value is 1e-16.
orthantwise_c	Coeefficient for the L1 norm of variables. This parameter should be set to zero for standard minimization problems. Setting this parameter to a positive value activates Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) method. Default value is 0.
orthantwise_start	Start index for computing L1 norm of the variables. This parameter is valid only for OWL-QN method. Default value is 0.
orthantwise_end	End index for computing L1 norm of the variables. Default value is 1.

在文件 LBFGSMinimizer.cpp 第 58 行定义.

virtual void set_penalty_type ( Penalty * penalty_type )

virtualinherited

Set the type of penalty For example, L2 penalty

参数

penalty_type the type of penalty. If NULL is given, regularization is not enabled.

在文件 FirstOrderMinimizer.h 第 137 行定义.

virtual void set_penalty_weight ( float64_t penalty_weight )

virtualinherited

Set the weight of penalty

参数

penalty_weight the weight of penalty, which is positive

在文件 FirstOrderMinimizer.h 第 126 行定义.

virtual bool supports_batch_update ( ) const

virtual

Does minimizer support batch update?

返回: whether minimizer supports batch update

实现了 FirstOrderMinimizer.

在文件 LBFGSMinimizer.h 第 73 行定义.

virtual void update_context ( CMinimizerContext * context )

protectedvirtualinherited

Update a context object to store mutable variables

参数

context a context object

被 FirstOrderStochasticMinimizer, SMDMinimizer , 以及 SMIDASMinimizer 重载.

在文件 FirstOrderMinimizer.h 第 147 行定义.

virtual void update_gradient	(	SGVector< float64_t >	gradient,
		SGVector< float64_t >	var
	)

protectedvirtualinherited

Add gradient of the penalty wrt target variables to unpenalized gradient For least sqaure with L2 penalty,

\[ L2f(w)=f(w) + L2(w) \]

where \( f(w)=\sum_i{(y_i-w^T x_i)^2}\) is the least sqaure cost function and \(L2(w)=\lambda \frac{w^t w}{2}\) is the L2 penalty

Target variables is \(w\) Unpenalized gradient is \(\frac{\partial f(w) }{\partial w}\) Gradient of the penalty wrt target variables is \(\frac{\partial L2(w) }{\partial w}\)

参数

gradient	unpenalized gradient wrt its target variable
var	the target variable

在文件 FirstOrderMinimizer.h 第 190 行定义.

类成员变量说明

float64_t m_delta

protected

Delta for convergence test based on the change of function value.

在文件 LBFGSMinimizer.h 第 174 行定义.

float64_t m_epsilon

protected

Epsilon for convergence test based on the change of gradient.

在文件 LBFGSMinimizer.h 第 180 行定义.

float64_t m_ftol

protected

A parameter used in Armijo condition.

在文件 LBFGSMinimizer.h 第 189 行定义.

FirstOrderCostFunction* m_fun

protectedinherited

Cost function

在文件 FirstOrderMinimizer.h 第 205 行定义.

float64_t m_gtol

protected

A parameter used in Morethuente linesearch to control the accuracy.

在文件 LBFGSMinimizer.h 第 195 行定义.

int m_linesearch

protected

The line search algorithm.

在文件 LBFGSMinimizer.h 第 168 行定义.

int m_m

protected

The number of corrections to approximate the inverse hessian matrix.

在文件 LBFGSMinimizer.h 第 162 行定义.

int m_max_iterations

protected

The maximum number of iterations for L-BFGS update.

在文件 LBFGSMinimizer.h 第 171 行定义.

int m_max_linesearch

protected

The maximum number of trials to do line search for each L-BFGS update.

在文件 LBFGSMinimizer.h 第 165 行定义.

float64_t m_max_step

protected

The maximum step of the line search.

在文件 LBFGSMinimizer.h 第 186 行定义.

float64_t m_min_step

protected

The minimum step of the line search.

在文件 LBFGSMinimizer.h 第 183 行定义.

float64_t m_orthantwise_c

protected

Coeefficient for the L1 norm of variables.

在文件 LBFGSMinimizer.h 第 201 行定义.

int m_orthantwise_end

protected

End index for computing L1 norm of the variables.

在文件 LBFGSMinimizer.h 第 207 行定义.

int m_orthantwise_start

protected

Start index for computing L1 norm of the variables.

在文件 LBFGSMinimizer.h 第 204 行定义.

int m_past

protected

Distance for delta-based convergence test.

在文件 LBFGSMinimizer.h 第 177 行定义.

Penalty* m_penalty_type

protectedinherited

the type of penalty

在文件 FirstOrderMinimizer.h 第 208 行定义.

float64_t m_penalty_weight

protectedinherited

the weight of penalty

在文件 FirstOrderMinimizer.h 第 211 行定义.

SGVector<float64_t> m_target_variable

protected

Target variable

在文件 LBFGSMinimizer.h 第 210 行定义.

float64_t m_wolfe

protected

A parameter used in curvature condition.

在文件 LBFGSMinimizer.h 第 192 行定义.

float64_t m_xtol

protected

The machine precision for floating-point values.

在文件 LBFGSMinimizer.h 第 198 行定义.

该类的文档由以下文件生成:

详细描述

Public 成员函数

Protected 成员函数

Protected 属性

构造及析构函数说明

成员函数说明

类成员变量说明