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N

n - Variable in class jml.matlab.utils.SingularValueDecompositionImpl
 
n - Static variable in class jml.optimization.PrimalDualInteriorPoint
Number of unknown variables
n - Variable in class jml.regression.Regression
Number of samples.
N - Variable in class jml.sequence.HMM
Number of states in the model.
N - Variable in class jml.sequence.HMMModel
Number of states in the model.
nClass - Variable in class jml.classification.Classifier
Number of classes.
nClass - Variable in class jml.classification.MaxEntModel
Number of classes.
nClass - Variable in class jml.feature.selection.SupervisedFeatureSelection
Number of classes.
nClass - Variable in class jml.options.Options
 
nClus - Variable in class jml.clustering.Clustering
Number of clusters.
nClus - Variable in class jml.options.ClusteringOptions
 
nClus - Variable in class jml.options.KMeansOptions
 
nClus - Variable in class jml.options.Options
 
nd - Variable in class jml.topics.LdaGibbsSampler
nd[i][j] number of words in document i assigned to topic j.
nDoc - Variable in class jml.options.Options
 
nDoc - Variable in class jml.topics.Corpus
Number of documents in the corpus.
ndsum - Variable in class jml.topics.LdaGibbsSampler
ndsum[i] total number of words in document i.
ne(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Do element by element comparisons between X and Y and returns a matrix of the same size with elements set to 1 where the relation is true and elements set to 0 where it is not.
ne(RealMatrix, double) - Static method in class jml.matlab.Matlab
Do element by element comparisons between X and x and returns a matrix of the same size with elements set to 1 where the relation is true and elements set to 0 where it is not.
ne(double, RealMatrix) - Static method in class jml.matlab.Matlab
Do element by element comparisons between x and X and returns a matrix of the same size with elements set to 1 where the relation is true and elements set to 0 where it is not.
nExample - Variable in class jml.classification.Classifier
Number of samples.
nFeature - Variable in class jml.classification.Classifier
Number of features, without bias dummy features, i.e., for SVM.
nFeature - Variable in class jml.classification.MaxEntModel
Number of features, without bias dummy features, i.e., for SVM.
nFeature - Variable in class jml.clustering.Clustering
Number of features.
nFeature - Variable in class jml.options.Options
 
NMF - Class in jml.clustering
A Java implementation for NMF which solves the following optimization problem:
NMF(Options) - Constructor for class jml.clustering.NMF
 
NMF(NMFOptions) - Constructor for class jml.clustering.NMF
 
NMF() - Constructor for class jml.clustering.NMF
 
NMFOptions - Class in jml.options
 
NMFOptions() - Constructor for class jml.options.NMFOptions
 
NMFOptions(NMFOptions) - Constructor for class jml.options.NMFOptions
 
NMFOptions(int) - Constructor for class jml.options.NMFOptions
 
NMFOptions(int, boolean, int) - Constructor for class jml.options.NMFOptions
 
NMFOptions(ClusteringOptions) - Constructor for class jml.options.NMFOptions
 
NonlinearConjugateGradient - Class in jml.optimization
A Java implementation for the nonlinear conjugate gradient method.
NonlinearConjugateGradient() - Constructor for class jml.optimization.NonlinearConjugateGradient
 
NonnegativePLBFGS - Class in jml.optimization
A Java implementation for the projected limited-memory BFGS algorithm with nonnegative constraints.
NonnegativePLBFGS() - Constructor for class jml.optimization.NonnegativePLBFGS
 
nonSingular - Variable in class jml.matlab.utils.SingularValueDecompositionImpl.Solver
Singularity indicator.
norm(RealMatrix, String) - Static method in class jml.matlab.Matlab
Calculate the Frobenius norm of a matrix A.
norm(RealMatrix, int) - Static method in class jml.matlab.Matlab
Compute the norm of a matrix or a vector.
norm(RealMatrix, double) - Static method in class jml.matlab.Matlab
Compute the induced vector norm of a matrix or a vector.
norm(RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the induced 2-norm of a matrix A or 2-norm of a vector.
normalizeByColumns(RealMatrix) - Static method in class jml.matlab.Matlab
Normalize A by columns.
normalizeByRows(RealMatrix) - Static method in class jml.matlab.Matlab
Normalize A by rows.
NormalizedCut - Class in jml.graph.cut
 
NormalizedCut(int) - Constructor for class jml.graph.cut.NormalizedCut
 
not(RealMatrix) - Static method in class jml.matlab.Matlab
Performs a logical NOT of input array X, and returns an array containing elements set to either 1 (TRUE) or 0 (FALSE).
nSample - Variable in class jml.clustering.Clustering
Number of samples.
nTerm - Variable in class jml.options.LDAOptions
 
nTerm - Variable in class jml.options.Options
 
nTerm - Variable in class jml.topics.Corpus
Vocabulary size.
nTopic - Variable in class jml.options.LDAOptions
 
nTopic - Variable in class jml.options.Options
 
nTopic - Variable in class jml.topics.TopicModel
Number of topics.
nTopTerm - Variable in class jml.options.Options
 
nu_opt - Variable in class jml.optimization.QPSolution
 
numStates - Variable in class jml.sequence.CRF
Number of states in the state space.
numStates - Variable in class jml.sequence.CRFModel
Number of states in the state space.
numstats - Variable in class jml.topics.LdaGibbsSampler
size of statistics
nw - Variable in class jml.topics.LdaGibbsSampler
nw[i][j] number of instances of term i assigned to topic j.
nwsum - Variable in class jml.topics.LdaGibbsSampler
nwsum[j] total number of words assigned to topic j.
ny - Variable in class jml.regression.Regression
Number of dependent variables.

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