Uses of Interface
jsat.math.Function

Packages that use Function

Package	Description
jsat.classifiers.linear
jsat.classifiers.neuralnetwork
jsat.distributions
jsat.distributions.discrete
jsat.linear
jsat.math
jsat.math.integration
jsat.math.optimization
jsat.math.optimization.oned
jsat.math.rootfinding
jsat.text.wordweighting

Uses of Function in jsat.classifiers.linear

Classes in jsat.classifiers.linear that implement Function

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

Uses of Function in jsat.classifiers.neuralnetwork

Classes in jsat.classifiers.neuralnetwork that implement Function

Modifier and Type	Class and Description
static class	BackPropagationNet.ActivationFunction The neural network needs an activation function for the neurons that is used to predict from inputs and train the network by propagating the errors back through the network.

Methods in jsat.classifiers.neuralnetwork that return Function

Modifier and Type	Method and Description
abstract Function	BackPropagationNet.ActivationFunction.getD() Returns the function object for the derivative of this activation function.

Uses of Function in jsat.distributions

Methods in jsat.distributions that return Function

Modifier and Type	Method and Description
static Function	Distribution.getFunctionCDF(Distribution dist) Wraps the Distribution.cdf(double) function of the given distribution in a function object for use.
static Function	ContinuousDistribution.getFunctionPDF(ContinuousDistribution dist) Wraps the ContinuousDistribution.pdf(double) function of the given distribution in a function object for use.

Methods in jsat.distributions with parameters of type Function

Modifier and Type	Method and Description
protected double	Distribution.invCdf(double p, Function cdf) This method is provided as a quick helper function, as any CDF has a 1 to 1 mapping with an inverse, CDF.-1.

Uses of Function in jsat.distributions.discrete

Methods in jsat.distributions.discrete with parameters of type Function

Modifier and Type	Method and Description
protected double	DiscreteDistribution.invCdf(double p, Function cdf)

Uses of Function in jsat.linear

Methods in jsat.linear with parameters of type Function

Modifier and Type	Method and Description
static double	VecOps.accumulateSum(Vec w, Vec x, Vec y, Function f) Computes the result of ∑∀ i ∈ |w| wi f(xi-yi)
void	Vec.applyFunction(Function f) Applies the given function to each and every value in the vector.
void	SparseVector.applyFunction(Function f)

Uses of Function in jsat.math

Subinterfaces of Function in jsat.math

Modifier and Type	Interface and Description
interface	FunctionP FunctionP is the same as Function except it supports parallel computation of the result.

Classes in jsat.math that implement Function

Modifier and Type	Class and Description
class	FunctionBase Simple base abstract class for implementing a Function by implementing FunctionBase.f(double[]) to call the vector version.
class	IndexFunction

Fields in jsat.math declared as Function

Modifier and Type	Field and Description
static Function	MathTricks.absFunc Convenience object for taking the abs of the first index
static Function	MathTricks.expFunc Convenience object for taking the exp of the first index
static Function	MathTricks.invsFunc Convenience object for taking the inverse (x-1) of the first index.
static Function	MathTricks.logFunc Convenience object for taking the log of the first index
static Function	MathTricks.sqrdFunc Convenience object for taking the squared value of the first index
static Function	MathTricks.sqrtFunc Convenience object for taking the square root of the first index

Uses of Function in jsat.math.integration

Methods in jsat.math.integration with parameters of type Function

Modifier and Type	Method and Description
static double	Romberg.romb(Function f, double a, double b)
static double	Romberg.romb(Function f, double a, double b, int max)
static double	Trapezoidal.trapz(Function f, double a, double b, int N)

Uses of Function in jsat.math.optimization

Classes in jsat.math.optimization that implement Function

Modifier and Type	Class and Description
class	RosenbrockFunction The Rosenbrock function is a function with at least one minima with the value zero.

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

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)
static double	GoldenSearch.minimize(double eps, int maxIterations, double a, double b, int pos, Function f, double... args) Finds the local minimum of the function f.
Vec	Optimizer.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs) Performs optimization on the given inputs to find the minima of the function.
Vec	NelderMead.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs)
Vec	IterativelyReweightedLeastSquares.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs)
Vec	Optimizer.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs, ExecutorService threadpool) Performs optimization on the given inputs to find the minima of the function.
Vec	NelderMead.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs, ExecutorService threadpool)
Vec	IterativelyReweightedLeastSquares.optimize(double eps, int iterationLimit, Function f, Function fd, Vec vars, List<Vec> inputs, Vec outputs, ExecutorService threadpool)
Vec	NelderMead.optimize(double eps, int iterationLimit, Function f, List<Vec> initalPoints) Attempts to find the minimal value of the given function.
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)

Uses of Function in jsat.math.optimization.oned

Methods in jsat.math.optimization.oned with parameters of type Function

Modifier and Type	Method and Description
static double	GoldenSearch.findMin(double min, double max, Function f, double eps, int maxSteps) Attempts to numerically find the value x that minimizes the one dimensional function f(x) in the range [min, max].

Uses of Function in jsat.math.rootfinding

Methods in jsat.math.rootfinding with parameters of type Function

Modifier and Type	Method and Description
static double	Zeroin.root(double eps, double a, double b, Function f, double... args)
static double	Secant.root(double eps, double a, double b, Function f, double... args)
static double	RiddersMethod.root(double eps, double a, double b, Function f, double... args)
static double	Bisection.root(double eps, double a, double b, Function f, double... args)
static double	Zeroin.root(double eps, double a, double b, int pos, Function f, double... args)
static double	Secant.root(double eps, double a, double b, int pos, Function f, double... args)
static double	RiddersMethod.root(double eps, double a, double b, int pos, Function f, double... args)
static double	Bisection.root(double eps, double a, double b, int pos, Function f, double... args)
static double	Zeroin.root(double a, double b, Function f, double... args)
static double	Secant.root(double a, double b, Function f, double... args)
static double	RiddersMethod.root(double a, double b, Function f, double... args)
static double	Bisection.root(double a, double b, Function f, double... args) Uses the bisection method to find the argument of some function f for which f(args) = 0.
double	Zeroin.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, double... args)
double	Secant.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, double... args)
double	RootFinder.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, double... args) Attempts to numerical compute the root of a given function, such that f(args) = 0.
double	RiddersMethod.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, double... args)
double	Bisection.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, double... args)
double	Zeroin.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, Vec args)
double	Secant.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, Vec args)
double	RootFinder.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, Vec args) Attempts to numerical compute the root of a given function, such that f(args) = 0.
double	RiddersMethod.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, Vec args)
double	Bisection.root(double eps, int maxIterations, double[] initialGuesses, Function f, int pos, Vec args)
static double	Zeroin.root(double eps, int maxIterations, double a, double b, int pos, Function f, double... args) Performs root finding on the function f.
static double	Secant.root(double eps, int maxIterations, double x0, double x1, int pos, Function f, double... args)
static double	RiddersMethod.root(double eps, int maxIterations, double x1, double x2, int pos, Function f, double... args)
static double	Bisection.root(double eps, int maxIterations, double a, double b, int pos, Function f, double... args) Uses the bisection method to find the argument of some function f for which f(args) = 0.

Uses of Function in jsat.text.wordweighting

Classes in jsat.text.wordweighting that implement Function

Modifier and Type	Class and Description
class	BinaryWordPresent Provides a simple binary representation of bag-of-word vectors by simply marking a value 1.0 if the token is present, and 0.0 if the token is not present.
class	OkapiBM25 Implements the Okapi BM25 word weighting scheme.
class	TfIdf Applies Term Frequency Inverse Document Frequency (TF IDF) weighting to the word vectors.
class	WordCount Provides a simple representation of bag-of-word vectors by simply using the number of occurrences for a word in a document as the weight for said word.
class	WordWeighting WordWeighting is an index function specifically mean for modifying the values of a vectors used for a bag-of-words representation of text data.