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F

F - Variable in class jml.classification.MaxEnt
Feature matrix array.
f(RealMatrix, RealMatrix, RealMatrix, RealMatrix, RealMatrix) - Method in class jml.clustering.L1NMF
 
feasible - Variable in class jml.optimization.PhaseIResult
 
Feature - Class in jml.feature
 
Feature() - Constructor for class jml.feature.Feature
 
features - Variable in class jml.classification.MultiClassSVM
Feature 2D array, indices start from 1.
features2Matrix(Feature[][]) - Static method in class jml.classification.MultiClassSVM
Convert features to original data matrix.
features2Matrix(Feature[][], double) - Static method in class jml.classification.MultiClassSVM
Convert features to matrix including bias features if bias is nonnegative.
features2MatrixWithoutBias(Feature[][]) - Static method in class jml.classification.MultiClassSVM
Convert features to original data matrix.
features2MatrixWithoutBias(Feature[][], double) - Static method in class jml.classification.MultiClassSVM
Convert features to matrix excluding bias features if bias is nonnegative.
FeatureSelection - Class in jml.feature.selection
Abstract class for feature selection algorithms.
FeatureSelection() - Constructor for class jml.feature.selection.FeatureSelection
 
feedData(RealMatrix) - Method in class jml.classification.Classifier
Feed training data with original data matrix for this classifier.
feedData(double[][]) - Method in class jml.classification.Classifier
Feed training data for this classification method.
feedData(double[][][]) - Method in class jml.classification.MaxEnt
Feed features for this maximum entropy model.
feedData(RealMatrix[]) - Method in class jml.classification.MaxEnt
Feed features for this maximum entropy model.
feedData(RealMatrix) - Method in class jml.classification.MultiClassSVM
Feed training data with original data matrix for this classifier.
feedData(RealMatrix) - Method in class jml.clustering.Clustering
Feed training data for this clustering algorithm.
feedData(double[][]) - Method in class jml.clustering.Clustering
Feed training data for this feature selection algorithm.
feedData(RealMatrix) - Method in class jml.feature.selection.FeatureSelection
Feed data for this feature selection algorithm.
feedData(double[][]) - Method in class jml.feature.selection.FeatureSelection
Feed data for this feature selection algorithm.
feedData(RealMatrix) - Method in class jml.recovery.MatrixCompletion
Feed an observation matrix.
feedData(RealMatrix) - Method in class jml.recovery.RobustPCA
Feed an observation matrix.
feedData(RealMatrix) - Method in class jml.regression.Regression
Feed training data for the regression model.
feedData(double[][]) - Method in class jml.regression.Regression
Feed training data for this regression model.
feedData(RealMatrix[][][]) - Method in class jml.sequence.CRF
Feed data sequences for training.
feedData(int[][]) - Method in class jml.sequence.HMM
Feed observation sequences for training.
feedData(RealMatrix) - Method in class jml.subspace.DimensionalityReduction
 
feedData(double[][]) - Method in class jml.subspace.DimensionalityReduction
 
feedDependentVariables(RealMatrix) - Method in class jml.regression.Regression
Feed training dependent variables for this regression model.
feedDependentVariables(double[][]) - Method in class jml.regression.Regression
Feed training dependent variables for this regression model.
feedIndices(RealMatrix) - Method in class jml.recovery.MatrixCompletion
Feed indices of samples.
feedIndices(int[]) - Method in class jml.recovery.MatrixCompletion
Feed indices of samples.
feedLabels(int[]) - Method in class jml.classification.Classifier
Feed labels of training data to the classifier.
feedLabels(RealMatrix) - Method in class jml.classification.Classifier
Feed labels for training data from a matrix.
feedLabels(double[][]) - Method in class jml.classification.Classifier
Feed labels for this classification method.
feedLabels(RealMatrix) - Method in class jml.feature.selection.SupervisedFeatureSelection
Feed labels for this supervised feature selection algorithm.
feedLabels(double[][]) - Method in class jml.feature.selection.SupervisedFeatureSelection
Feed labels for this supervised feature selection algorithm.
feedLabels(int[]) - Method in class jml.feature.selection.SupervisedFeatureSelection
Feed labels for this supervised feature selection algorithm.
feedLabels(int[][]) - Method in class jml.sequence.CRF
Feed labels for training data sequences.
feedLabels(int[][]) - Method in class jml.sequence.HMM
Feed state sequences for training data.
feedProblem(ArrayList<String>) - Method in class jml.classification.MultiClassSVM
Feed a problem from a string array.
feedProblem(String) - Method in class jml.classification.MultiClassSVM
Feed a problem from a file with the LIBLINEAR input data format.
feedProblem(Problem) - Method in class jml.classification.MultiClassSVM
Feed a problem for this SVM classifier.
Figure - Class in jml.visualization
 
Figure() - Constructor for class jml.visualization.Figure
 
find(RealVector) - Static method in class jml.matlab.Matlab
Find nonzero elements and return their indices.
find(RealMatrix) - Static method in class jml.matlab.Matlab
Find nonzero elements and return their value, row and column indices.
find2(RealMatrix) - Static method in class jml.matlab.Matlab
Find nonzero elements and return their value, row and column indices.
FindResult - Class in jml.matlab.utils
A wrapper for the output of find function.
FindResult(int[], int[], double[]) - Constructor for class jml.matlab.utils.FindResult
 
first - Variable in class jml.matlab.utils.Pair
 
fix(double) - Static method in class jml.matlab.Matlab
Round towards zero.
fix(RealMatrix) - Static method in class jml.matlab.Matlab
Round elements of a matrix A towards zero to.
floor(RealMatrix) - Static method in class jml.matlab.Matlab
Round towards minus infinity of elements of a matrix A.
formula - Static variable in class jml.optimization.NonlinearConjugateGradient
Formula used to calculate beta.
fprintf(String, Object...) - Static method in class jml.matlab.Matlab
Write a formatted string to the standard output (the screen).
Fs - Variable in class jml.sequence.CRF
A 3D RealMatrix array, where F[k][i][j] is the sparse feature matrix for the j-th feature of the k-th observation sequence at position i, i.e., f_{j}^{{\bf x}_k, i}.
full(RealMatrix) - Static method in class jml.matlab.Matlab
Convert a sparse matrix into a dense matrix.
fval - Static variable in class jml.optimization.BoundConstrainedPLBFGS
The last objective function value.
fval - Static variable in class jml.optimization.LBFGS
The last objective function value.
fval - Static variable in class jml.optimization.LBFGSOnSimplex
The last objective function value.
fval - Static variable in class jml.optimization.NonlinearConjugateGradient
The last objective function value.
fval - Static variable in class jml.optimization.NonnegativePLBFGS
The last objective function value.
fval_Y_k - Static variable in class jml.optimization.AcceleratedProximalGradient
f(Y_k) = g(Y_k) + h(Y_k).

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