Index

B C D E F G H I L M N O P R S T V X Y
All Classes|All Packages

B

bias - Variable in class de.bwaldvogel.liblinear.Problem

If bias >= 0, we assume that one additional feature is added to the end of each data instance

C

C_times_loss(int, double) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvrFunction

clone() - Method in class de.bwaldvogel.liblinear.Parameter

crossValidation(Problem, Parameter, int, double[]) - Static method in class de.bwaldvogel.liblinear.Linear

D

de.bwaldvogel.liblinear - package de.bwaldvogel.liblinear

disableDebugOutput() - Static method in class de.bwaldvogel.liblinear.Linear

E

enableDebugOutput() - Static method in class de.bwaldvogel.liblinear.Linear

equals(Object) - Method in class de.bwaldvogel.liblinear.FeatureNode

equals(Object) - Method in class de.bwaldvogel.liblinear.Model

F

Feature - Interface in de.bwaldvogel.liblinear

FeatureNode - Class in de.bwaldvogel.liblinear

FeatureNode(int, double) - Constructor for class de.bwaldvogel.liblinear.FeatureNode

find_parameter_C(Problem, Parameter, double, double, int[], int[], Problem[], int) - Static method in class de.bwaldvogel.liblinear.Linear

findParameters(Problem, Parameter, int, double, double) - Static method in class de.bwaldvogel.liblinear.Linear

G

getBestC() - Method in class de.bwaldvogel.liblinear.ParameterCSearchResult

getBestC() - Method in class de.bwaldvogel.liblinear.ParameterSearchResult

getBestP() - Method in class de.bwaldvogel.liblinear.ParameterSearchResult

getBestScore() - Method in class de.bwaldvogel.liblinear.ParameterCSearchResult

getBestScore() - Method in class de.bwaldvogel.liblinear.ParameterSearchResult

getBias() - Method in class de.bwaldvogel.liblinear.Model

getBias() - Method in class de.bwaldvogel.liblinear.Train

getById(int) - Static method in enum de.bwaldvogel.liblinear.SolverType

getC() - Method in class de.bwaldvogel.liblinear.Parameter

getDecfunBias(int) - Method in class de.bwaldvogel.liblinear.Model

This function gives the bias term corresponding to the class with the label_idx.

getDecfunCoef(int, int) - Method in class de.bwaldvogel.liblinear.Model

This function gives the coefficient for the feature with feature index = feat_idx and the class with label index = label_idx.

getDecfunRho() - Method in class de.bwaldvogel.liblinear.Model

This function gives rho, the bias term used in one-class SVM only.

getEps() - Method in class de.bwaldvogel.liblinear.Parameter

getFeatureWeights() - Method in class de.bwaldvogel.liblinear.Model

The array w gives feature weights; its size is nr_feature*nr_class but is nr_feature if nr_class = 2.

getId() - Method in enum de.bwaldvogel.liblinear.SolverType

getIndex() - Method in interface de.bwaldvogel.liblinear.Feature

getIndex() - Method in class de.bwaldvogel.liblinear.FeatureNode

getInitSol() - Method in class de.bwaldvogel.liblinear.Parameter

getLabels() - Method in class de.bwaldvogel.liblinear.Model

getLine() - Method in exception de.bwaldvogel.liblinear.InvalidInputDataException

getMaxIters() - Method in class de.bwaldvogel.liblinear.Parameter

getNrClass() - Method in class de.bwaldvogel.liblinear.Model

getNrFeature() - Method in class de.bwaldvogel.liblinear.Model

getNu() - Method in class de.bwaldvogel.liblinear.Parameter

getNumWeights() - Method in class de.bwaldvogel.liblinear.Parameter

the number of weights

getP() - Method in class de.bwaldvogel.liblinear.Parameter

getParameter() - Method in class de.bwaldvogel.liblinear.Train

getProblem() - Method in class de.bwaldvogel.liblinear.Train

getSolverType() - Method in class de.bwaldvogel.liblinear.Model

getSolverType() - Method in class de.bwaldvogel.liblinear.Parameter

getValue() - Method in interface de.bwaldvogel.liblinear.Feature

getValue() - Method in class de.bwaldvogel.liblinear.FeatureNode

getVersion() - Static method in class de.bwaldvogel.liblinear.Linear

getWeightLabels() - Method in class de.bwaldvogel.liblinear.Parameter

getWeights() - Method in class de.bwaldvogel.liblinear.Parameter

grad(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvrFunction

H

hashCode() - Method in class de.bwaldvogel.liblinear.FeatureNode

hashCode() - Method in class de.bwaldvogel.liblinear.Model

I

index - Variable in class de.bwaldvogel.liblinear.FeatureNode

InvalidInputDataException - Exception in de.bwaldvogel.liblinear

InvalidInputDataException(String, int) - Constructor for exception de.bwaldvogel.liblinear.InvalidInputDataException

InvalidInputDataException(String, int, Exception) - Constructor for exception de.bwaldvogel.liblinear.InvalidInputDataException

isLogisticRegressionSolver() - Method in enum de.bwaldvogel.liblinear.SolverType

isOneClass() - Method in enum de.bwaldvogel.liblinear.SolverType

isProbabilityModel() - Method in class de.bwaldvogel.liblinear.Model

isRegularizeBias() - Method in class de.bwaldvogel.liblinear.Parameter

isSupportVectorRegression() - Method in enum de.bwaldvogel.liblinear.SolverType

L

l - Variable in class de.bwaldvogel.liblinear.Problem

the number of training data

L1R_L2LOSS_SVC - de.bwaldvogel.liblinear.SolverType

L1-regularized L2-loss support vector classification

L1R_LR - de.bwaldvogel.liblinear.SolverType

L1-regularized logistic regression

L2R_L1LOSS_SVC_DUAL - de.bwaldvogel.liblinear.SolverType

L2-regularized L1-loss support vector classification (dual) (fka L1LOSS_SVM_DUAL)

L2R_L1LOSS_SVR_DUAL - de.bwaldvogel.liblinear.SolverType

L2-regularized L2-loss support vector regression (primal)

L2R_L2_SvrFunction - Class in de.bwaldvogel.liblinear

L2R_L2_SvrFunction(Problem, Parameter, double[]) - Constructor for class de.bwaldvogel.liblinear.L2R_L2_SvrFunction

L2R_L2LOSS_SVC - de.bwaldvogel.liblinear.SolverType

L2-regularized L2-loss support vector classification (primal) (fka L2LOSS_SVM)

L2R_L2LOSS_SVC_DUAL - de.bwaldvogel.liblinear.SolverType

L2-regularized L2-loss support vector classification (dual) (fka L2LOSS_SVM_DUAL)

L2R_L2LOSS_SVR - de.bwaldvogel.liblinear.SolverType

L2-regularized L2-loss support vector regression (dual)

L2R_L2LOSS_SVR_DUAL - de.bwaldvogel.liblinear.SolverType

L2-regularized L1-loss support vector regression (dual)

L2R_LR - de.bwaldvogel.liblinear.SolverType

L2-regularized logistic regression (primal) (fka L2_LR)

L2R_LR_DUAL - de.bwaldvogel.liblinear.SolverType

L2-regularized logistic regression (dual)

Linear - Class in de.bwaldvogel.liblinear

Java port of liblinear

Linear() - Constructor for class de.bwaldvogel.liblinear.Linear

load(File) - Static method in class de.bwaldvogel.liblinear.Model

Deprecated.

use Model.load(Path) instead

load(Reader) - Static method in class de.bwaldvogel.liblinear.Model

see Linear.loadModel(Reader)

load(Path) - Static method in class de.bwaldvogel.liblinear.Model

see Linear.loadModel(Path)

loadModel(File) - Static method in class de.bwaldvogel.liblinear.Linear

Deprecated.

use Linear.loadModel(Path) instead

loadModel(Reader) - Static method in class de.bwaldvogel.liblinear.Linear

Loads the model from inputReader.

loadModel(Path) - Static method in class de.bwaldvogel.liblinear.Linear

Loads the model from the file with ISO-8859-1 charset.

M

main(String[]) - Static method in class de.bwaldvogel.liblinear.Predict

main(String[]) - Static method in class de.bwaldvogel.liblinear.Train

MCSVM_CS - de.bwaldvogel.liblinear.SolverType

multi-class support vector classification by Crammer and Singer

Model - Class in de.bwaldvogel.liblinear

Model stores the model obtained from the training procedure

Model() - Constructor for class de.bwaldvogel.liblinear.Model

N

n - Variable in class de.bwaldvogel.liblinear.Problem

the number of features (including the bias feature if bias >= 0)

O

ONECLASS_SVM - de.bwaldvogel.liblinear.SolverType

one-class support vector machine (dual)

P

Parameter - Class in de.bwaldvogel.liblinear

Parameter(SolverType, double, double) - Constructor for class de.bwaldvogel.liblinear.Parameter

Parameter(SolverType, double, double, double) - Constructor for class de.bwaldvogel.liblinear.Parameter

Parameter(SolverType, double, double, int, double) - Constructor for class de.bwaldvogel.liblinear.Parameter

Parameter(SolverType, double, int, double) - Constructor for class de.bwaldvogel.liblinear.Parameter

ParameterCSearchResult - Class in de.bwaldvogel.liblinear

ParameterCSearchResult(double, double) - Constructor for class de.bwaldvogel.liblinear.ParameterCSearchResult

ParameterSearchResult - Class in de.bwaldvogel.liblinear

ParameterSearchResult(double, double, double) - Constructor for class de.bwaldvogel.liblinear.ParameterSearchResult

parse_command_line(String[]) - Method in class de.bwaldvogel.liblinear.Train

predict(Model, Feature[]) - Static method in class de.bwaldvogel.liblinear.Linear

Predict - Class in de.bwaldvogel.liblinear

Predict() - Constructor for class de.bwaldvogel.liblinear.Predict

predictProbability(Model, Feature[], double[]) - Static method in class de.bwaldvogel.liblinear.Linear

predictValues(Model, Feature[], double[]) - Static method in class de.bwaldvogel.liblinear.Linear

Problem - Class in de.bwaldvogel.liblinear

Describes the problem

Problem() - Constructor for class de.bwaldvogel.liblinear.Problem

R

readFromFile(File, double) - Static method in class de.bwaldvogel.liblinear.Problem

Deprecated.

use Problem.readFromFile(Path, double) instead

readFromFile(File, Charset, double) - Static method in class de.bwaldvogel.liblinear.Problem

Deprecated.

use Problem.readFromFile(Path, Charset, double) instead

readFromFile(Path, double) - Static method in class de.bwaldvogel.liblinear.Problem

see readProblem(Path, double)

readFromFile(Path, Charset, double) - Static method in class de.bwaldvogel.liblinear.Problem

see readProblem(Path, Charset, double)

readFromStream(InputStream, double) - Static method in class de.bwaldvogel.liblinear.Problem

see readProblem(InputStream, double)

readFromStream(InputStream, Charset, double) - Static method in class de.bwaldvogel.liblinear.Problem

see readProblem(InputStream, Charset, double)

readProblem(File, double) - Static method in class de.bwaldvogel.liblinear.Train

Deprecated.

use readProblem(Path, double) instead

readProblem(File, Charset, double) - Static method in class de.bwaldvogel.liblinear.Train

Deprecated.

use readProblem(Path, Charset, double) instead

readProblem(InputStream, double) - Static method in class de.bwaldvogel.liblinear.Train

readProblem(InputStream, Charset, double) - Static method in class de.bwaldvogel.liblinear.Train

readProblem(String) - Method in class de.bwaldvogel.liblinear.Train

readProblem(String, double) - Method in class de.bwaldvogel.liblinear.Train

readProblem(Path) - Method in class de.bwaldvogel.liblinear.Train

readProblem(Path, double) - Static method in class de.bwaldvogel.liblinear.Train

reads a problem from LibSVM format

readProblem(Path, Charset, double) - Static method in class de.bwaldvogel.liblinear.Train

resetRandom() - Static method in class de.bwaldvogel.liblinear.Linear

resets the PRNG this is i.a.

S

save(File) - Method in class de.bwaldvogel.liblinear.Model

Deprecated.

use Model.save(Path) instead

save(Writer) - Method in class de.bwaldvogel.liblinear.Model

see Linear.saveModel(Writer, Model)

save(Path) - Method in class de.bwaldvogel.liblinear.Model

see Linear.saveModel(Path, Model)

saveModel(File, Model) - Static method in class de.bwaldvogel.liblinear.Linear

Deprecated.

use Linear.saveModel(Path, Model) instead

saveModel(Writer, Model) - Static method in class de.bwaldvogel.liblinear.Linear

Writes the model to the modelOutput.

saveModel(Path, Model) - Static method in class de.bwaldvogel.liblinear.Linear

Writes the model to the file with ISO-8859-1 charset.

setC(double) - Method in class de.bwaldvogel.liblinear.Parameter

C is the cost of constraints violation.

setDebugOutput(PrintStream) - Static method in class de.bwaldvogel.liblinear.Linear

setEps(double) - Method in class de.bwaldvogel.liblinear.Parameter

eps is the stopping criterion.

setInitSol(double[]) - Method in class de.bwaldvogel.liblinear.Parameter

setMaxIters(int) - Method in class de.bwaldvogel.liblinear.Parameter

setNu(double) - Method in class de.bwaldvogel.liblinear.Parameter

setP(double) - Method in class de.bwaldvogel.liblinear.Parameter

set the epsilon in loss function of epsilon-SVR (default 0.1)

setRegularizeBias(boolean) - Method in class de.bwaldvogel.liblinear.Parameter

setSolverType(SolverType) - Method in class de.bwaldvogel.liblinear.Parameter

setValue(double) - Method in interface de.bwaldvogel.liblinear.Feature

setValue(double) - Method in class de.bwaldvogel.liblinear.FeatureNode

setWeights(double[], int[]) - Method in class de.bwaldvogel.liblinear.Parameter

nr_weight, weight_label, and weight are used to change the penalty for some classes (If the weight for a class is not changed, it is set to 1).

SolverType - Enum in de.bwaldvogel.liblinear

T

toString() - Method in class de.bwaldvogel.liblinear.FeatureNode

toString() - Method in exception de.bwaldvogel.liblinear.InvalidInputDataException

toString() - Method in class de.bwaldvogel.liblinear.Model

train(Problem, Parameter) - Static method in class de.bwaldvogel.liblinear.Linear

Train - Class in de.bwaldvogel.liblinear

Train() - Constructor for class de.bwaldvogel.liblinear.Train

V

value - Variable in class de.bwaldvogel.liblinear.FeatureNode

valueOf(String) - Static method in enum de.bwaldvogel.liblinear.SolverType

Returns the enum constant of this type with the specified name.

values() - Static method in enum de.bwaldvogel.liblinear.SolverType

Returns an array containing the constants of this enum type, in the order they are declared.

X

x - Variable in class de.bwaldvogel.liblinear.Problem

array of sparse feature nodes

Y

y - Variable in class de.bwaldvogel.liblinear.Problem

an array containing the target values

B C D E F G H I L M N O P R S T V X Y
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