A B C D E F G H I L M N O P R S T V W X Y _
All Classes All Packages
All Classes All Packages
All Classes All Packages
A
- a - Variable in class de.bwaldvogel.liblinear.Heap
- addToArray(double[], double) - Static method in class de.bwaldvogel.liblinear.Train
- addToArray(int[], int) - Static method in class de.bwaldvogel.liblinear.Train
- arrayEquals(double[], double[]) - Static method in class de.bwaldvogel.liblinear.Model
-
don't use
Arrays.equals(double[], double[])
here, cause 0.0 and -0.0 should be handled the same - arrayHashCode(double[]) - Static method in class de.bwaldvogel.liblinear.Model
-
see
Arrays.hashCode(double[])
but treat 0.0 and -0.0 the same - ArraySorter - Class in de.bwaldvogel.liblinear
- ArraySorter() - Constructor for class de.bwaldvogel.liblinear.ArraySorter
- atof(String) - Static method in class de.bwaldvogel.liblinear.Linear
- atoi(String) - Static method in class de.bwaldvogel.liblinear.Linear
- axpy(double, Feature[], double[]) - Static method in class de.bwaldvogel.liblinear.SparseOperator
B
- B - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- be_shrunk(int, int, int, double, double) - Method in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- bestC - Variable in class de.bwaldvogel.liblinear.ParameterCSearchResult
- bestC - Variable in class de.bwaldvogel.liblinear.ParameterSearchResult
- bestP - Variable in class de.bwaldvogel.liblinear.ParameterSearchResult
- bestScore - Variable in class de.bwaldvogel.liblinear.ParameterCSearchResult
- bestScore - Variable in class de.bwaldvogel.liblinear.ParameterSearchResult
- bias - Variable in class de.bwaldvogel.liblinear.Model
- 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
- bias - Variable in class de.bwaldvogel.liblinear.Train
- Blas - Class in de.bwaldvogel.liblinear
- Blas() - Constructor for class de.bwaldvogel.liblinear.Blas
C
- C - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
- C - Variable in class de.bwaldvogel.liblinear.Parameter
- C - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- C_specified - Variable in class de.bwaldvogel.liblinear.Train
- C_times_loss(int, double) - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
- C_times_loss(int, double) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- C_times_loss(int, double) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvrFunction
- C_times_loss(int, double) - Method in class de.bwaldvogel.liblinear.L2R_LrFunction
- calc_max_p(Problem) - Static method in class de.bwaldvogel.liblinear.Linear
- calc_start_C(Problem, Parameter) - Static method in class de.bwaldvogel.liblinear.Linear
- checkProblemSize(int, int) - Static method in class de.bwaldvogel.liblinear.Linear
-
verify the size and throw an exception early if the problem is too large
- clone() - Method in class de.bwaldvogel.liblinear.Parameter
- cmp(Feature, Feature) - Method in class de.bwaldvogel.liblinear.Heap
- COLON - Static variable in class de.bwaldvogel.liblinear.Predict
- constructProblem(List<Double>, List<Feature[]>, int, double) - Static method in class de.bwaldvogel.liblinear.Train
- count - Variable in class de.bwaldvogel.liblinear.Linear.GroupClassesReturn
- cross_validation - Variable in class de.bwaldvogel.liblinear.Train
- crossValidation(Problem, Parameter, int, double[]) - Static method in class de.bwaldvogel.liblinear.Linear
D
- D - Variable in class de.bwaldvogel.liblinear.L2R_LrFunction
- daxpy_(int, double, double[], int, double[], int) - Static method in class de.bwaldvogel.liblinear.Blas
- daxpy_(MutableInt, MutableDouble, double[], MutableInt, double[], MutableInt) - Static method in class de.bwaldvogel.liblinear.Blas
- ddot_(int, double[], int, double[], int) - Static method in class de.bwaldvogel.liblinear.Blas
- ddot_(MutableInt, double[], MutableInt, double[], MutableInt) - Static method in class de.bwaldvogel.liblinear.Blas
- de.bwaldvogel.liblinear - package de.bwaldvogel.liblinear
- DEBUG_OUTPUT - Static variable in class de.bwaldvogel.liblinear.Linear
- deepClone(Random) - Static method in class de.bwaldvogel.liblinear.Parameter
- DEFAULT_LOCALE - Static variable in class de.bwaldvogel.liblinear.Linear
- DEFAULT_RANDOM_SEED - Static variable in class de.bwaldvogel.liblinear.Parameter
- disableDebugOutput() - Static method in class de.bwaldvogel.liblinear.Linear
- dnrm2_(int, double[], MutableInt) - Static method in class de.bwaldvogel.liblinear.Blas
- dnrm2_(MutableInt, double[], MutableInt) - Static method in class de.bwaldvogel.liblinear.Blas
- do_cross_validation() - Method in class de.bwaldvogel.liblinear.Train
- do_find_parameters() - Method in class de.bwaldvogel.liblinear.Train
- doPredict(BufferedReader, Writer, Model, boolean) - Static method in class de.bwaldvogel.liblinear.Predict
-
Note: The streams are NOT closed
- dot(double[], Feature[]) - Static method in class de.bwaldvogel.liblinear.SparseOperator
- DoubleArrayPointer - Class in de.bwaldvogel.liblinear
- DoubleArrayPointer(double[], int) - Constructor for class de.bwaldvogel.liblinear.DoubleArrayPointer
- dscal_(int, double, double[], int) - Static method in class de.bwaldvogel.liblinear.Blas
- dscal_(MutableInt, MutableDouble, double[], MutableInt) - Static method in class de.bwaldvogel.liblinear.Blas
E
- enableDebugOutput() - Static method in class de.bwaldvogel.liblinear.Linear
- eps - Variable in class de.bwaldvogel.liblinear.Newton
- eps - Variable in class de.bwaldvogel.liblinear.Parameter
-
stopping tolerance
- eps - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- eps_cg - Variable in class de.bwaldvogel.liblinear.Newton
- equals(Object) - Method in class de.bwaldvogel.liblinear.FeatureNode
- equals(Object) - Method in class de.bwaldvogel.liblinear.Model
- exit_with_help() - Static method in class de.bwaldvogel.liblinear.Predict
- exit_with_help() - Method in class de.bwaldvogel.liblinear.Train
F
- Feature - Interface in de.bwaldvogel.liblinear
- FeatureNode - Class in de.bwaldvogel.liblinear
- FeatureNode(int, double) - Constructor for class de.bwaldvogel.liblinear.FeatureNode
- FeatureNode(int, double, boolean) - Constructor for class de.bwaldvogel.liblinear.FeatureNode
- FILE_CHARSET - Static variable in class de.bwaldvogel.liblinear.Linear
- find_parameter_C(Problem, Parameter, double, double, int[], int[], Problem[], int) - Static method in class de.bwaldvogel.liblinear.Linear
- find_parameters - Variable in class de.bwaldvogel.liblinear.Train
- findParameters(Problem, Parameter, int, double, double) - Static method in class de.bwaldvogel.liblinear.Linear
- fun(double[]) - Method in interface de.bwaldvogel.liblinear.Function
- fun(double[]) - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
- fun_obj - Variable in class de.bwaldvogel.liblinear.Newton
- Function - Interface in de.bwaldvogel.liblinear
G
- G - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- get() - Method in class de.bwaldvogel.liblinear.MutableDouble
- get() - Method in class de.bwaldvogel.liblinear.MutableInt
- get(int) - Method in class de.bwaldvogel.liblinear.DoubleArrayPointer
- get(int) - Method in class de.bwaldvogel.liblinear.IntArrayPointer
- get_diag_preconditioner(double[]) - Method in interface de.bwaldvogel.liblinear.Function
- get_diag_preconditioner(double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- get_diag_preconditioner(double[]) - Method in class de.bwaldvogel.liblinear.L2R_LrFunction
- get_nr_variable() - Method in interface de.bwaldvogel.liblinear.Function
- get_nr_variable() - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
- get_w_value(int, int) - Method in class de.bwaldvogel.liblinear.Model
- 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.
- GETI(byte[], int) - Static method in class de.bwaldvogel.liblinear.Linear
- GETI(int) - Method in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- GETI_SVR(int) - Static method in class de.bwaldvogel.liblinear.Linear
- 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
- getNumFolds() - Method in class de.bwaldvogel.liblinear.Train
- 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 interface de.bwaldvogel.liblinear.Function
- grad(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- grad(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvrFunction
- grad(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_LrFunction
- groupClasses(Problem, int[]) - Static method in class de.bwaldvogel.liblinear.Linear
- GroupClassesReturn(int, int[], int[], int[]) - Constructor for class de.bwaldvogel.liblinear.Linear.GroupClassesReturn
H
- hashCode() - Method in class de.bwaldvogel.liblinear.FeatureNode
- hashCode() - Method in class de.bwaldvogel.liblinear.Model
- Heap - Class in de.bwaldvogel.liblinear
- Heap(int, Heap.HeapType) - Constructor for class de.bwaldvogel.liblinear.Heap
- Heap.HeapType - Enum in de.bwaldvogel.liblinear
- HeapType() - Constructor for enum de.bwaldvogel.liblinear.Heap.HeapType
- Hv(double[], double[]) - Method in interface de.bwaldvogel.liblinear.Function
- Hv(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- Hv(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_LrFunction
I
- I - Variable in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- id - Variable in enum de.bwaldvogel.liblinear.SolverType
- index - Variable in class de.bwaldvogel.liblinear.FeatureNode
- info(String) - Static method in class de.bwaldvogel.liblinear.Linear
- info(String, Object...) - Static method in class de.bwaldvogel.liblinear.Linear
- init_sol - Variable in class de.bwaldvogel.liblinear.Parameter
-
Initial-solution specification (only supported for
L2R_LR
andL2R_L2LOSS_SVC
) - initialized - Variable in class de.bwaldvogel.liblinear.MutableDouble
- initialized - Variable in class de.bwaldvogel.liblinear.MutableInt
- inputFilename - Variable in class de.bwaldvogel.liblinear.Train
- IntArrayPointer - Class in de.bwaldvogel.liblinear
- IntArrayPointer(int[], int) - Constructor for class de.bwaldvogel.liblinear.IntArrayPointer
- 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
- isFindParameters() - Method in class de.bwaldvogel.liblinear.Train
- 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
- l - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- 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_ErmFunction - Class in de.bwaldvogel.liblinear
- L2R_ErmFunction(Problem, Parameter, double[]) - Constructor for class de.bwaldvogel.liblinear.L2R_ErmFunction
- 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_SvcFunction - Class in de.bwaldvogel.liblinear
- L2R_L2_SvcFunction(Problem, Parameter, double[]) - Constructor for class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- 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)
- L2R_LrFunction - Class in de.bwaldvogel.liblinear
- L2R_LrFunction(Problem, Parameter, double[]) - Constructor for class de.bwaldvogel.liblinear.L2R_LrFunction
- label - Variable in class de.bwaldvogel.liblinear.Linear.GroupClassesReturn
- label - Variable in class de.bwaldvogel.liblinear.Model
-
label of each class
- Linear - Class in de.bwaldvogel.liblinear
-
Java port of liblinear
- Linear() - Constructor for class de.bwaldvogel.liblinear.Linear
- Linear.GroupClassesReturn - Class in de.bwaldvogel.liblinear
-
used as complex return type
- linesearch_and_update(double[], double[], MutableDouble, double[], double) - Method in interface de.bwaldvogel.liblinear.Function
- linesearch_and_update(double[], double[], MutableDouble, double[], double) - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
- 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
- load(Path) - Static method in class de.bwaldvogel.liblinear.Model
- 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.
- logisticRegressionSolver - Variable in enum de.bwaldvogel.liblinear.SolverType
M
- main(String[]) - Static method in class de.bwaldvogel.liblinear.Predict
- main(String[]) - Static method in class de.bwaldvogel.liblinear.Train
- MAX - de.bwaldvogel.liblinear.Heap.HeapType
- max_iter - Variable in class de.bwaldvogel.liblinear.Newton
- max_iter - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- max_iters - Variable in class de.bwaldvogel.liblinear.Parameter
- MCSVM_CS - de.bwaldvogel.liblinear.SolverType
-
multi-class support vector classification by Crammer and Singer
- med3(double[], int, int, int) - Static method in class de.bwaldvogel.liblinear.ArraySorter
-
Returns the index of the median of the three indexed doubles.
- MIN - de.bwaldvogel.liblinear.Heap.HeapType
- Model - Class in de.bwaldvogel.liblinear
-
Model stores the model obtained from the training procedure
- Model() - Constructor for class de.bwaldvogel.liblinear.Model
- modelFilename - Variable in class de.bwaldvogel.liblinear.Train
- MutableDouble - Class in de.bwaldvogel.liblinear
- MutableDouble() - Constructor for class de.bwaldvogel.liblinear.MutableDouble
- MutableDouble(double) - Constructor for class de.bwaldvogel.liblinear.MutableDouble
- MutableInt - Class in de.bwaldvogel.liblinear
- MutableInt(int) - Constructor for class de.bwaldvogel.liblinear.MutableInt
N
- n - Variable in class de.bwaldvogel.liblinear.Problem
-
the number of features (including the bias feature if bias >= 0)
- newton(double[]) - Method in class de.bwaldvogel.liblinear.Newton
- Newton - Class in de.bwaldvogel.liblinear
- Newton(Function, double, int) - Constructor for class de.bwaldvogel.liblinear.Newton
- Newton(Function, double, int, double) - Constructor for class de.bwaldvogel.liblinear.Newton
- nr_class - Variable in class de.bwaldvogel.liblinear.Linear.GroupClassesReturn
- nr_class - Variable in class de.bwaldvogel.liblinear.Model
- nr_class - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- nr_feature - Variable in class de.bwaldvogel.liblinear.Model
- nr_fold - Variable in class de.bwaldvogel.liblinear.Train
- nrm2_sq(Feature[]) - Static method in class de.bwaldvogel.liblinear.SparseOperator
- nu - Variable in class de.bwaldvogel.liblinear.Parameter
O
- ONECLASS_SVM - de.bwaldvogel.liblinear.SolverType
-
one-class support vector machine (dual)
- OUTPUT_MUTEX - Static variable in class de.bwaldvogel.liblinear.Linear
P
- p - Variable in class de.bwaldvogel.liblinear.L2R_L2_SvrFunction
- p - Variable in class de.bwaldvogel.liblinear.Parameter
- P_specified - Variable in class de.bwaldvogel.liblinear.Train
- param - Variable in class de.bwaldvogel.liblinear.Train
- 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
- pcg(double[], double[], double[], double[]) - Method in class de.bwaldvogel.liblinear.Newton
- pop() - Method in class de.bwaldvogel.liblinear.Heap
- 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
- printf(Formatter, String, Object...) - Static method in class de.bwaldvogel.liblinear.Linear
- prob - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
- prob - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- prob - Variable in class de.bwaldvogel.liblinear.Train
- Problem - Class in de.bwaldvogel.liblinear
-
Describes the problem
- Problem() - Constructor for class de.bwaldvogel.liblinear.Problem
- push(Feature) - Method in class de.bwaldvogel.liblinear.Heap
R
- random - Variable in class de.bwaldvogel.liblinear.Parameter
- random - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- 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
- readFromFile(Path, Charset, double) - Static method in class de.bwaldvogel.liblinear.Problem
- readFromStream(InputStream, double) - Static method in class de.bwaldvogel.liblinear.Problem
- readFromStream(InputStream, Charset, double) - Static method in class de.bwaldvogel.liblinear.Problem
- readProblem(File, double) - Static method in class de.bwaldvogel.liblinear.Train
-
Deprecated.use
Train.readProblem(Path, double)
instead - readProblem(File, Charset, double) - Static method in class de.bwaldvogel.liblinear.Train
-
Deprecated.use
Train.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
- regularize_bias - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
- regularize_bias - Variable in class de.bwaldvogel.liblinear.Parameter
- resetRandom() - Static method in class de.bwaldvogel.liblinear.Linear
-
Deprecated.Use
Parameter.setRandom(Random)
instead - reversedMergesort(double[]) - Static method in class de.bwaldvogel.liblinear.ArraySorter
-
Sorts the specified array of doubles into descending order.
- reversedMergesort(double[], int, int) - Static method in class de.bwaldvogel.liblinear.ArraySorter
- rho - Variable in class de.bwaldvogel.liblinear.Model
-
one-class SVM only
- run(String[]) - Method in class de.bwaldvogel.liblinear.Train
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
- save(Path) - Method in class de.bwaldvogel.liblinear.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.
- serialVersionUID - Static variable in exception de.bwaldvogel.liblinear.InvalidInputDataException
- serialVersionUID - Static variable in class de.bwaldvogel.liblinear.Model
- set(double) - Method in class de.bwaldvogel.liblinear.MutableDouble
- set(int) - Method in class de.bwaldvogel.liblinear.MutableInt
- set(int, double) - Method in class de.bwaldvogel.liblinear.DoubleArrayPointer
- set(int, int) - Method in class de.bwaldvogel.liblinear.IntArrayPointer
- 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
- setOffset(int) - Method in class de.bwaldvogel.liblinear.DoubleArrayPointer
- setOffset(int) - Method in class de.bwaldvogel.liblinear.IntArrayPointer
- setP(double) - Method in class de.bwaldvogel.liblinear.Parameter
-
set the epsilon in loss function of epsilon-SVR (default 0.1)
- setRandom(Random) - Method in class de.bwaldvogel.liblinear.Parameter
- 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).
- size - Variable in class de.bwaldvogel.liblinear.Heap
- size() - Method in class de.bwaldvogel.liblinear.Heap
- sizeI - Variable in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- solve(double[]) - Method in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- solve_l1r_l2_svc(Problem, Parameter, double[], double, double, double, int) - Static method in class de.bwaldvogel.liblinear.Linear
-
A coordinate descent algorithm for L1-regularized L2-loss support vector classification
- solve_l1r_lr(Problem, Parameter, double[], double, double, double, int) - Static method in class de.bwaldvogel.liblinear.Linear
-
A coordinate descent algorithm for L1-regularized logistic regression problems
- solve_l2r_l1l2_svc(Problem, Parameter, double[], double, double, int) - Static method in class de.bwaldvogel.liblinear.Linear
-
A coordinate descent algorithm for L1-loss and L2-loss SVM dual problems
- solve_l2r_l1l2_svr(Problem, Parameter, double[], int) - Static method in class de.bwaldvogel.liblinear.Linear
-
A coordinate descent algorithm for L1-loss and L2-loss epsilon-SVR dual problem min_\beta 0.5\beta^T (Q + diag(lambda)) \beta - p \sum_{i=1}^l|\beta_i| + \sum_{i=1}^l yi\beta_i, s.t.
- solve_l2r_lr_dual(Problem, Parameter, double[], double, double, int) - Static method in class de.bwaldvogel.liblinear.Linear
-
A coordinate descent algorithm for the dual of L2-regularized logistic regression problems
- solve_oneclass_svm(Problem, Parameter, double[], MutableDouble, int) - Static method in class de.bwaldvogel.liblinear.Linear
- solve_sub_problem(double, int, double, int, double[]) - Method in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- solver_specified - Variable in class de.bwaldvogel.liblinear.Train
- SolverMCSVM_CS - Class in de.bwaldvogel.liblinear
-
A coordinate descent algorithm for multi-class support vector machines by Crammer and Singer
- SolverMCSVM_CS(Problem, int, double[], double, Random) - Constructor for class de.bwaldvogel.liblinear.SolverMCSVM_CS
- SOLVERS_BY_ID - Static variable in enum de.bwaldvogel.liblinear.SolverType
- solverType - Variable in class de.bwaldvogel.liblinear.Model
- solverType - Variable in class de.bwaldvogel.liblinear.Parameter
- SolverType - Enum in de.bwaldvogel.liblinear
- SolverType(int, boolean, boolean) - Constructor for enum de.bwaldvogel.liblinear.SolverType
- sparse_dot(Feature[], Feature[]) - Static method in class de.bwaldvogel.liblinear.SparseOperator
- SparseOperator - Class in de.bwaldvogel.liblinear
- SparseOperator() - Constructor for class de.bwaldvogel.liblinear.SparseOperator
- start - Variable in class de.bwaldvogel.liblinear.Linear.GroupClassesReturn
- subXTv(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_L2_SvcFunction
- supportVectorRegression - Variable in enum de.bwaldvogel.liblinear.SolverType
- swap(double[], int, int) - Static method in class de.bwaldvogel.liblinear.ArraySorter
-
Swaps x[a] with x[b].
- swap(double[], int, int) - Static method in class de.bwaldvogel.liblinear.Linear
- swap(int[], int, int) - Static method in class de.bwaldvogel.liblinear.Linear
- swap(Feature[], int, int) - Static method in class de.bwaldvogel.liblinear.Linear
- swap(IntArrayPointer, int, int) - Static method in class de.bwaldvogel.liblinear.Linear
T
- tmp - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
- top() - Method in class de.bwaldvogel.liblinear.Heap
- 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
- train_one(Problem, Parameter, double[], double, double) - Static method in class de.bwaldvogel.liblinear.Linear
- transpose(Problem) - Static method in class de.bwaldvogel.liblinear.Linear
- type - Variable in class de.bwaldvogel.liblinear.Heap
V
- value - Variable in class de.bwaldvogel.liblinear.FeatureNode
- value - Variable in class de.bwaldvogel.liblinear.MutableDouble
- value - Variable in class de.bwaldvogel.liblinear.MutableInt
- valueOf(String) - Static method in enum de.bwaldvogel.liblinear.Heap.HeapType
-
Returns the enum constant of this type with the specified name.
- 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.Heap.HeapType
-
Returns an array containing the constants of this enum type, in the order they are declared.
- 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.
- vecswap(double[], int, int, int) - Static method in class de.bwaldvogel.liblinear.ArraySorter
-
Swaps x[a ..
- VERSION - Static variable in class de.bwaldvogel.liblinear.Linear
W
- w - Variable in class de.bwaldvogel.liblinear.Model
-
feature weight array
- w_size - Variable in class de.bwaldvogel.liblinear.SolverMCSVM_CS
- weight - Variable in class de.bwaldvogel.liblinear.Parameter
- weightLabel - Variable in class de.bwaldvogel.liblinear.Parameter
- wTw - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
- wx - Variable in class de.bwaldvogel.liblinear.L2R_ErmFunction
X
- x - Variable in class de.bwaldvogel.liblinear.Problem
-
array of sparse feature nodes
- XTv(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
- Xv(double[], double[]) - Method in class de.bwaldvogel.liblinear.L2R_ErmFunction
Y
_
- _array - Variable in class de.bwaldvogel.liblinear.DoubleArrayPointer
- _array - Variable in class de.bwaldvogel.liblinear.IntArrayPointer
- _line - Variable in exception de.bwaldvogel.liblinear.InvalidInputDataException
- _offset - Variable in class de.bwaldvogel.liblinear.DoubleArrayPointer
- _offset - Variable in class de.bwaldvogel.liblinear.IntArrayPointer
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