Uses of Interface
jsat.math.FunctionVec

Packages that use FunctionVec

Package	Description
jsat.classifiers.linear
jsat.math.optimization

Uses of FunctionVec in jsat.classifiers.linear

Classes in jsat.classifiers.linear that implement FunctionVec

Modifier and Type	Class and Description
class	LinearBatch.GradFunction Function for using the single weight vector loss functions related to LossC and LossR

Uses of FunctionVec in jsat.math.optimization

Fields in jsat.math.optimization declared as FunctionVec

Modifier and Type	Field and Description
static FunctionVec	RosenbrockFunction.GRADIENT The gradient of the Rosenbrock function

Methods in jsat.math.optimization that return FunctionVec

Modifier and Type	Method and Description
FunctionVec	RosenbrockFunction.getDerivative() Returns the gradient of the Rosenbrock function

Methods in jsat.math.optimization with parameters of type FunctionVec

Modifier and Type	Method and Description
double	WolfeNWLineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk)
double	LineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk) Attempts to find the value of α that minimizes f(x+α p)
double	BacktrackingArmijoLineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk)
double	WolfeNWLineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk, ExecutorService ex)
double	LineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk, ExecutorService ex) Attempts to find the value of α that minimizes f(x+α p)
double	BacktrackingArmijoLineSearch.lineSearch(double alpha_max, Vec x_k, Vec x_grad, Vec p_k, Function f, FunctionVec fp, double f_x, double gradP, Vec x_alpha_pk, double[] fxApRet, Vec grad_x_alpha_pk, ExecutorService ex)
void	Optimizer2.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp) Attempts to optimize the given function by finding the value of w that will minimize the value returned by f(w), using w = x0 as an initial starting point.
void	ModifiedOWLQN.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp)
void	LBFGS.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp)
void	BFGS.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp)
void	Optimizer2.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp, ExecutorService ex) Attempts to optimize the given function by finding the value of w that will minimize the value returned by f(w), using w = x0 as an initial starting point.
void	ModifiedOWLQN.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp, ExecutorService ex)
void	LBFGS.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp, ExecutorService ex)
void	BFGS.optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, FunctionVec fpp, ExecutorService ex)