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T

T - Variable in class jml.classification.AdaBoost
Number of iterations, or the number of weak classifiers.
t - Static variable in class jml.optimization.AcceleratedProximalGradient
Step length for backtracking line search.
t - Static variable in class jml.optimization.BoundConstrainedPLBFGS
Step length for backtracking line search.
t - Static variable in class jml.optimization.LBFGS
Step length for backtracking line search.
t - Static variable in class jml.optimization.LBFGSOnSimplex
Step length for backtracking line search.
t - Static variable in class jml.optimization.NonlinearConjugateGradient
Step length for backtracking line search.
t - Static variable in class jml.optimization.NonnegativePLBFGS
Step length for backtracking line search.
t - Static variable in class jml.optimization.PrimalDualInteriorPoint
 
t - Static variable in class jml.utils.Time
 
thetasum - Variable in class jml.topics.LdaGibbsSampler
cumulative statistics of theta
THIN_INTERVAL - Static variable in class jml.topics.LdaGibbsSampler
sampling lag (?)
thinInterval - Variable in class jml.options.LDAOptions
 
tic() - Static method in class jml.utils.Time
TSTART = TIC saves the time to an output argument, TSTART.
Time - Class in jml.utils
 
Time() - Constructor for class jml.utils.Time
 
times(RealMatrix, RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the element-wise multiplication of two matrices X and Y.
times(double, RealMatrix) - Static method in class jml.matlab.Matlab
Array multiplication between a scalar and a matrix.
times(RealMatrix, double) - Static method in class jml.matlab.Matlab
Array multiplication between a matrix and a scalar.
times(double, double) - Static method in class jml.matlab.Matlab
Scalar multiplication between two scalars a and b.
timesAssign(double[], double) - Static method in class jml.operation.ArrayOperation
Element-wise multiplication and assignment operation.
timesAssign(double[], double[]) - Static method in class jml.operation.ArrayOperation
Element-wise multiplication and assignment operation.
timesAssign(double[], double) - Method in class jml.sequence.HMM
Element-wise multiplication and assignment operation.
timesAssign(double[], double[]) - Method in class jml.sequence.HMM
Element-wise multiplication and assignment operation.
toc() - Static method in class jml.utils.Time
Calculate the elapsed time, in seconds, since the most recent execution of the TIC command.
toc(double) - Static method in class jml.utils.Time
TOC(TSTART) measures the time elapsed since the TIC command that generated TSTART.
tol - Static variable in class jml.optimization.BoundConstrainedPLBFGS
Tolerance of convergence.
tol - Static variable in class jml.optimization.LBFGSOnSimplex
Tolerance of convergence.
tol - Static variable in class jml.optimization.NonnegativePLBFGS
Tolerance of convergence.
topicMatrix - Variable in class jml.topics.TopicModel
A V-by-K matrix, where each column is a topic vector represented by a vector of weights.
TopicModel - Class in jml.topics
Abstract super class for all topic models.
TopicModel() - Constructor for class jml.topics.TopicModel
Default constructor for this topic model.
TopicModel(int) - Constructor for class jml.topics.TopicModel
Constructor for this topic model given the number of topics for a corpus.
toString() - Method in class jml.matlab.utils.Pair
 
trace(RealMatrix) - Static method in class jml.matlab.Matlab
Calculate the trace of a matrix A.
train() - Method in class jml.classification.AdaBoost
 
train() - Method in class jml.classification.Classifier
Train the classifier.
train() - Method in class jml.classification.LogisticRegressionMCBoundConstrainedPLBFGS
 
train() - Method in class jml.classification.LogisticRegressionMCGradientDescent
 
train() - Method in class jml.classification.LogisticRegressionMCLBFGS
 
train() - Method in class jml.classification.LogisticRegressionMCLBFGS_Ori
 
train() - Method in class jml.classification.LogisticRegressionMCNonlinearConjugateGradient
 
train() - Method in class jml.classification.LogisticRegressionMCNonnegativePLBFGS
 
train() - Method in class jml.classification.MaxEnt
 
train() - Method in class jml.classification.MultiClassSVM
 
train(RealMatrix, int) - Method in class jml.online.classification.OnlineBinaryClassifier
Train the classifier with a new sample X.
train(double[], int) - Method in class jml.online.classification.OnlineBinaryClassifier
Train the classifier with a new sample X.
train(RealMatrix, int) - Method in class jml.online.classification.Perceptron
 
train(RealMatrix, int) - Method in class jml.online.classification.Winnow
 
train() - Method in class jml.regression.LASSO
 
train(RealMatrix, RealMatrix, Options) - Static method in class jml.regression.LASSO
 
train(RealMatrix, RealMatrix) - Method in class jml.regression.LASSO
 
train() - Method in class jml.regression.Regression
Train the regression model.
train(RealMatrix, RealMatrix) - Method in class jml.regression.Regression
 
train() - Method in class jml.sequence.CRF
Estimate parameters for the basic CRF by a maximum conditional log-likelihood estimation principle.
train() - Method in class jml.sequence.HMM
Inference the basic HMM with scaling.
train() - Method in class jml.topics.LDA
 
train() - Method in class jml.topics.LSI
 
train() - Method in class jml.topics.SparseLSA
 
train() - Method in class jml.topics.TopicModel
Train this topic model to fit the given corpus.
transposed - Variable in class jml.matlab.utils.SingularValueDecompositionImpl
 
TwoDimArray2Matrix(ArrayList<double[]>) - Static method in class jml.data.Data
 

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