Index

A

ALP (class in frlearn.data_descriptors)

ALP.Model (class in frlearn.data_descriptors)

B

BallTree (class in frlearn.neighbour_search_methods)

BallTree.Model (class in frlearn.neighbour_search_methods)

C

CD (class in frlearn.data_descriptors) CD.Model (class in frlearn.data_descriptors)

ConstantWeights (class in frlearn.weights) contract() (in module frlearn.transformations)

D

div_or() (in module frlearn.array_functions)

E

ExponentialWeights (class in frlearn.weights)

F

first() (in module frlearn.array_functions) FRFS (class in frlearn.feature_preprocessors) FRFS.Model (class in frlearn.feature_preprocessors) FRNN (class in frlearn.classifiers) (class in frlearn.regressors) FRNN.Model (class in frlearn.classifiers) (class in frlearn.regressors)

FRONEC (class in frlearn.classifiers) FRONEC.Model (class in frlearn.classifiers) FROVOCO (class in frlearn.classifiers) FROVOCO.Model (class in frlearn.classifiers) FRPS (class in frlearn.instance_preprocessors)

G

goguen_t_norm() (in module frlearn.t_norms)

greatest() (in module frlearn.array_functions)

H

heyting_t_norm() (in module frlearn.t_norms)

I

IF (class in frlearn.data_descriptors) IF.Model (class in frlearn.data_descriptors)

interquartile_range() (in module frlearn.dispersion_measures) IQRNormaliser (class in frlearn.feature_preprocessors) IQRNormaliser.Model (class in frlearn.feature_preprocessors)

K

KDTree (class in frlearn.neighbour_search_methods)

KDTree.Model (class in frlearn.neighbour_search_methods)

L

last() (in module frlearn.array_functions) least() (in module frlearn.array_functions) LinearNormaliser (class in frlearn.feature_preprocessors) LinearNormaliser.Model (class in frlearn.feature_preprocessors) LinearWeights (class in frlearn.weights)

LNND (class in frlearn.data_descriptors) LNND.Model (class in frlearn.data_descriptors) LOF (class in frlearn.data_descriptors) LOF.Model (class in frlearn.data_descriptors) log_multiple() (in module frlearn.parametrisations) lukasiewicz_t_norm() (in module frlearn.t_norms)

M

MaxAbsNormaliser (class in frlearn.feature_preprocessors) MaxAbsNormaliser.Model (class in frlearn.feature_preprocessors) maximum() (in module frlearn.location_measures) maximum_absolute_value() (in module frlearn.dispersion_measures) MD (class in frlearn.data_descriptors) MD.Model (class in frlearn.data_descriptors)

mean() (in module frlearn.location_measures) median() (in module frlearn.location_measures) midhinge() (in module frlearn.location_measures) midrange() (in module frlearn.location_measures) minimum() (in module frlearn.location_measures) MinkowskiSize (class in frlearn.vector_size_measures) multiple() (in module frlearn.parametrisations)

N

NND (class in frlearn.data_descriptors)

NND.Model (class in frlearn.data_descriptors)

Q

QuantifierWeights (class in frlearn.weights)

R

RangeNormaliser (class in frlearn.feature_preprocessors) RangeNormaliser.Model (class in frlearn.feature_preprocessors)

ReciprocallyLinearWeights (class in frlearn.weights) remove_diagonal() (in module frlearn.array_functions)

S

shifted_reciprocal() (in module frlearn.transformations) soft_head() (in module frlearn.array_functions) soft_max() (in module frlearn.array_functions) soft_min() (in module frlearn.array_functions) soft_tail() (in module frlearn.array_functions)

standard_deviation() (in module frlearn.dispersion_measures) Standardiser (class in frlearn.feature_preprocessors) Standardiser.Model (class in frlearn.feature_preprocessors) SVM (class in frlearn.data_descriptors) SVM.Model (class in frlearn.data_descriptors)

T

total_range() (in module frlearn.dispersion_measures)

truncated_complement() (in module frlearn.transformations)

V

VectorSizeNormaliser (class in frlearn.feature_preprocessors)

VectorSizeNormaliser.Model (class in frlearn.feature_preprocessors)

W

Weights (class in frlearn.weights)