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S

SchurmannGrassbergerEntropy - Class in be.ac.ulb.mlg.utils.measure.entropy
Schurmann-Grassberger entropy estimate of Dirichlet probability distribution.
SchurmannGrassbergerEntropy() - Constructor for class be.ac.ulb.mlg.utils.measure.entropy.SchurmannGrassbergerEntropy
 
setGroup(int, String) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define the group for one input data vector
setGroup(int, int) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define the group for one input data vector
setGroups(int[], int) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define the group of all input data vectors by their indexes
setGroupsNames(int, String[]) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define groups and associate them a label.
setHandelingMissingValues(boolean) - Method in class be.ac.ulb.mlg.utils.Measurer
Define the checking of missing values
setMaximumMissingValues(int) - Method in class be.ac.ulb.mlg.utils.Measurer
Define the number of maximum allowed missing values
setNormalizer(String, int, double) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define a specific value to use instead of the sum by column for groups
setNormalizer(int, int, double) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define a specific value to use instead of the sum by column for groups
setNormalizer(int, double) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Define a specific value to use instead of the sum by column
setNumberOfThreads(int) - Method in class be.ac.ulb.mlg.utils.Measurer
Define the number of threads to be used
setRenormalizer(Renormalizer) - Method in class be.ac.ulb.mlg.utils.Measurer
Define the renormalizer object
setTaxa(String[]) - Method in class be.ac.ulb.mlg.utils.renormalizer.TaxonRenormalizer
Set the taxa for all row (null or out of taxon results in considering the row as a feature)
setUp() - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizerTest
 
setup(double[], boolean) - Method in class be.ac.ulb.mlg.utils.measure.kernel.GaussianKernel
 
setup(double[], boolean) - Method in interface be.ac.ulb.mlg.utils.measure.Kernel
Setup the Kernel for a specific vector
setUp() - Method in class be.ac.ulb.mlg.utils.MeasurerTest
 
setUp() - Method in class be.ac.ulb.mlg.utils.renormalizer.TaxonRenormalizerTest
 
ShannonEntropy - Class in be.ac.ulb.mlg.utils.measure.entropy
Shannon entropy estimate (empirical) of Uniform probability distribution.
ShannonEntropy() - Constructor for class be.ac.ulb.mlg.utils.measure.entropy.ShannonEntropy
 
shufflePair() - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
 
shufflePair() - Method in interface be.ac.ulb.mlg.utils.Renormalizer
Know if the measurer use pre-shuffle
simulateRenormalization(double[], double[], int, int) - Method in class be.ac.ulb.mlg.utils.DefaultRenormalizer
 
simulateRenormalization(double[], double[], int, int) - Method in interface be.ac.ulb.mlg.utils.Renormalizer
Method called when pairwise renormalization is used in order to obtain a normalized version of the shuffled vector as if it was in the original input matrix
Spearman - Class in be.ac.ulb.mlg.utils.measure
 
Spearman() - Constructor for class be.ac.ulb.mlg.utils.measure.Spearman
 
sqrt(double) - Static method in class be.ac.ulb.mlg.utils.MeasureUtils
Compute the square root value by using the formula exp(0.5*log(x)) <=> sqrt(x) in order to avoid underflow.
Steinhaus - Class in be.ac.ulb.mlg.utils.measure
Steinhaus(X,Y) = 2*W/(sum(X)+sum(Y)), with W = sum_i[ min(x_i,y_i)]
Steinhaus() - Constructor for class be.ac.ulb.mlg.utils.measure.Steinhaus
 
SUM_NORMILIZER - Static variable in class be.ac.ulb.mlg.utils.DefaultRenormalizer
Sentinel value meaning that the renormalizer use the sum function on columns

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