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M

m - Variable in class jml.matlab.utils.SingularValueDecompositionImpl
 
m - Static variable in class jml.optimization.BoundConstrainedPLBFGS
 
m - Static variable in class jml.optimization.LBFGS
 
m - Static variable in class jml.optimization.LBFGSOnSimplex
 
m - Static variable in class jml.optimization.NonnegativePLBFGS
 
m - Static variable in class jml.optimization.PrimalDualInteriorPoint
Number of inequality constraints
M - Variable in class jml.sequence.HMM
Number of distinct observation symbols per state.
M - Variable in class jml.sequence.HMMModel
Number of distinct observation symbols per state.
main(String[]) - Static method in class jml.classification.AdaBoost
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCBoundConstrainedPLBFGS
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCGradientDescent
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCLBFGS
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCLBFGS_Ori
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCNonlinearConjugateGradient
 
main(String[]) - Static method in class jml.classification.LogisticRegressionMCNonnegativePLBFGS
 
main(String[]) - Static method in class jml.classification.MaxEnt
 
main(String[]) - Static method in class jml.classification.MultiClassSVM
 
main(String[]) - Static method in class jml.clustering.KMeans
 
main(String[]) - Static method in class jml.clustering.L1NMF
 
main(String[]) - Static method in class jml.clustering.LLNMF
 
main(String[]) - Static method in class jml.clustering.MRNMF
 
main(String[]) - Static method in class jml.clustering.NMF
 
main(String[]) - Static method in class jml.clustering.SpectralClustering
 
main(String[]) - Static method in class jml.data.Data
 
main(String[]) - Static method in class jml.feature.Feature
 
main(String[]) - Static method in class jml.feature.selection.JointL21NormsMinimization
 
main(String[]) - Static method in class jml.graph.cut.MinMaxCut
 
main(String[]) - Static method in class jml.graph.cut.NormalizedCut
 
main(String[]) - Static method in class jml.graph.cut.RatioCut
 
main(String[]) - Static method in class jml.JML
Main class entry called from a command line.
main(String[]) - Static method in class jml.kernel.Kernel
 
main(String[]) - Static method in class jml.manifold.Manifold
 
main(String[]) - Static method in class jml.matlab.Matlab
 
main(String[]) - Static method in class jml.online.classification.Perceptron
 
main(String[]) - Static method in class jml.online.classification.Winnow
 
main(String[]) - Static method in class jml.optimization.AcceleratedProximalGradient
 
main(String[]) - Static method in class jml.optimization.GeneralQP
 
main(String[]) - Static method in class jml.optimization.GeneralQPViaPrimalDualInteriorPoint
 
main(String[]) - Static method in class jml.optimization.LBFGSOnSimplex
 
main(String[]) - Static method in class jml.optimization.PrimalDualInteriorPoint
 
main(String[]) - Static method in class jml.optimization.ProjL1
 
main(String[]) - Static method in class jml.optimization.ProxLInfinity
 
main(String[]) - Static method in class jml.optimization.QPWithBoundConstraints
 
main(String[]) - Static method in class jml.random.MultivariateGaussianDistribution
 
main(String[]) - Static method in class jml.recovery.MatrixCompletion
 
main(String[]) - Static method in class jml.recovery.RobustPCA
 
main(String[]) - Static method in class jml.regression.LASSO
 
main(String[]) - Static method in class jml.sequence.CRF
 
main(String[]) - Static method in class jml.sequence.HMM
 
main(String[]) - Static method in class jml.subspace.Isomap
 
main(String[]) - Static method in class jml.subspace.KernelPCA
 
main(String[]) - Static method in class jml.subspace.LaplacianEigenmaps
 
main(String[]) - Static method in class jml.subspace.LLE
 
main(String[]) - Static method in class jml.subspace.MDS
 
main(String[]) - Static method in class jml.subspace.PCA
 
main(String[]) - Static method in class jml.topics.LDA
 
main(String[]) - Static method in class jml.topics.LdaGibbsSampler
Driver with example data.
main(String[]) - Static method in class jml.topics.LSI
 
main(String[]) - Static method in class jml.topics.SparseLSA
 
main(String[]) - Static method in class jml.visualization.Figure
 
Manifold - Class in jml.manifold
 
Manifold() - Constructor for class jml.manifold.Manifold
 
mapArray2Matrix(ArrayList<TreeMap<Integer, Double>>) - Static method in class jml.data.Data
 
Matlab - Class in jml.matlab
Matlab provides some frequently used Matlab matrix functions such as sort, sum, max, min, kron, vec, repmat, reshape, and colon.
Matlab() - Constructor for class jml.matlab.Matlab
 
Matrix - Static variable in class jml.optimization.PrimalDualInteriorPoint
 
matrix2Features(RealMatrix) - Static method in class jml.classification.MultiClassSVM
Convert original data matrix into Feature[][] including bias features.
matrix2Features(RealMatrix, double) - Static method in class jml.classification.MultiClassSVM
Convert original data matrix into Feature[][] including bias features if bias is nonnegative.
MatrixCompletion - Class in jml.recovery
A Java implementation of matrix completion which solves the following convex optimization problem:
min ||A||_*
s.t.
MatrixCompletion() - Constructor for class jml.recovery.MatrixCompletion
Constructor.
matrixCompletion(RealMatrix, RealMatrix) - Method in class jml.recovery.MatrixCompletion
Do matrix completion which solves the following convex optimization problem:
min ||A||_*
s.t.
matrixCompletion(RealMatrix, int[]) - Method in class jml.recovery.MatrixCompletion
Do matrix completion which solves the following convex optimization problem:
min ||A||_*
s.t.
max(RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the maximum of a row matrix A or its column-wise maximum.
max(RealMatrix, double) - Static method in class jml.matlab.Matlab
Calculate maximum between elements of A and a real number and return as a matrix with the same shape of A.
max(double, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate maximum between elements of A and a real number and return as a matrix with the same shape of A.
max(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate element-wise maximum between two matrices X and Y.
max(RealMatrix, int) - Static method in class jml.matlab.Matlab
Calculate the maximal value and its row or column index of a matrix A.
max(RealVector) - Static method in class jml.matlab.Matlab
Get the maximal value and its index in V.
max1(RealMatrix, int) - Static method in class jml.matlab.Matlab
Deprecated. 
max2(RealMatrix, int) - Static method in class jml.matlab.Matlab
Deprecated. 
MaxEnt - Class in jml.classification
A Java implementation for the maximum entropy modeling.
MaxEnt() - Constructor for class jml.classification.MaxEnt
 
MaxEntModel - Class in jml.classification
Maximum entropy model parameters.
MaxEntModel(int, RealMatrix, int[]) - Constructor for class jml.classification.MaxEntModel
Constructor for a MaxEnt model.
maxIter - Variable in class jml.clustering.L1NMF
 
maxIter - Variable in class jml.options.ClusteringOptions
 
maxIter - Variable in class jml.options.KMeansOptions
 
maxIter - Variable in class jml.options.Options
 
maxIter - Variable in class jml.regression.Regression
Maximal number of iterations.
maxIter - Variable in class jml.sequence.CRF
Maximal number of iterations.
maxIter - Variable in class jml.sequence.HMM
Maximal number of iterations.
MDS - Class in jml.subspace
Multi-dimensional Scaling (MDS).
MDS(int) - Constructor for class jml.subspace.MDS
Constructor.
mean(RealMatrix) - Static method in class jml.matlab.Matlab
Average or mean value of array.
mean(RealMatrix, int) - Static method in class jml.matlab.Matlab
M = mean(A, dim) returns the mean values for elements along the dimension of A specified by scalar dim.
min(RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the minimum of a row matrix A or its column-wise minimum.
min(RealMatrix, double) - Static method in class jml.matlab.Matlab
Calculate minimum between elements of A and a real number and return as a matrix with the same shape of A.
min(double, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate minimum between elements of A and a real number and return as a matrix with the same shape of A.
min(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate element-wise minimum between two matrices X and Y.
min(RealMatrix, int) - Static method in class jml.matlab.Matlab
Calculate the minimal value and its row and column index of a matrix A.
min(RealVector) - Static method in class jml.matlab.Matlab
Get the minimal value and its index in V.
min1(RealMatrix, int) - Static method in class jml.matlab.Matlab
Deprecated. 
min2(RealMatrix, int) - Static method in class jml.matlab.Matlab
Deprecated. 
MinMaxCut - Class in jml.graph.cut
 
MinMaxCut(int) - Constructor for class jml.graph.cut.MinMaxCut
 
minus(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Array subtraction between two matrices.
minus(RealMatrix, double) - Static method in class jml.matlab.Matlab
Array subtraction between a matrix and a scalar.
minus(double, RealMatrix) - Static method in class jml.matlab.Matlab
Array subtraction between a scalar and a matrix.
minus(double, double) - Static method in class jml.matlab.Matlab
Subtraction between two scalars a and b.
minusAssign(int[], int) - Static method in class jml.operation.ArrayOperation
Element-wise subtraction and assignment operation.
minusAssign(double[], double) - Static method in class jml.operation.ArrayOperation
Element-wise subtraction and assignment operation.
minusAssign(double[], double[]) - Static method in class jml.operation.ArrayOperation
Element-wise subtraction and assignment operation.
mldivide(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the left division of the form A \ B.
model - Variable in class jml.classification.LogisticRegressionMCLBFGS
 
Model - Class in jml.classification
 
Model(RealMatrix) - Constructor for class jml.classification.Model
 
model - Variable in class jml.classification.MultiClassSVM
SVM model.
mrdivide(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the right division of B into A, i.e., A / B.
MRNMF - Class in jml.clustering
 
MRNMF() - Constructor for class jml.clustering.MRNMF
 
mtimes(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Matrix multiplication.
mtimes(RealMatrix, double) - Static method in class jml.matlab.Matlab
Matrix multiplication.
mtimes(double, RealMatrix) - Static method in class jml.matlab.Matlab
Matrix multiplication.
mu - Variable in class jml.clustering.L1NMF
 
mu - Static variable in class jml.optimization.PrimalDualInteriorPoint
 
mu - Variable in class jml.options.L1NMFOptions
 
mu - Variable in class jml.options.Options
 
MultiClassSVM - Class in jml.classification
Multi-class SVM using LIBLINEAR library.
MultiClassSVM(double, double) - Constructor for class jml.classification.MultiClassSVM
Maximal feature index, not including the bias feature.
MultiClassSVM() - Constructor for class jml.classification.MultiClassSVM
 
MultivariateGaussianDistribution - Class in jml.random
A Java implementation for the multivariate Gaussian distribution given mean and covariance.
MultivariateGaussianDistribution() - Constructor for class jml.random.MultivariateGaussianDistribution
 
mvnrnd(RealMatrix, RealMatrix, int) - Static method in class jml.matlab.Matlab
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and covariance SIGMA.
mvnrnd(double[], double[][], int) - Static method in class jml.matlab.Matlab
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and covariance SIGMA.
mvnrnd(double[], double[], int) - Static method in class jml.matlab.Matlab
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and a diagonal covariance SIGMA.
mvnrnd(RealMatrix, RealMatrix, int) - Static method in class jml.random.MultivariateGaussianDistribution
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and covariance SIGMA.
mvnrnd(double[], double[][], int) - Static method in class jml.random.MultivariateGaussianDistribution
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and covariance SIGMA.
mvnrnd(double[], double[], int) - Static method in class jml.random.MultivariateGaussianDistribution
Generate random samples chosen from the multivariate Gaussian distribution with mean MU and a diagonal covariance SIGMA.

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