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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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