Release history¶
Version 0.2.2¶
Changelog¶
Bug fixes
Version 0.2.1¶
Changelog¶
Bug fixes
Rename abstract base class ModelFactory to SoftMachine
Version 0.2¶
Changelog¶
Adds core set of data descriptors, basic feature preprocessors and first regressor, thoroughly revised api.
New algorithms¶
data descriptors:
ALP
CD
EIF (wrapper requiring optional eif dependency
IF (wrapper for scikit-learn implementation)
LNND
LOF
MD
NND
SVM (wrapper for scikit-learn implementation)
feature preprocessors:
LinearNormaliser
IQRNormaliser
MaxAbsNormaliser
RangeNormaliser
Standardiser
SAE (requires optional tensorflow dependency)
VectorSizeNormaliser
regressors:
FRNN
API changes¶
Uniform ModelFactory pattern: callable algorithms that create callable models.
Preprocessors can be included at initialisation and are applied automatically.
Algorithms are presented no longer by submodule (neighbours, trees, etc), but by type (classifiers, feature preprocessors, etc)
Many changes and additions to secondary functions that can be used to parametrise the main algorithms.
Version 0.1¶
Changelog¶
Adds number of existing fuzzy rough set algorithms.
New algorithms¶
FRFS
FRONEC
FROVOCO
FRPS
API changes¶
neighbours.FRNNClassifier replaced by neighbours.FRNN.
Classifiers give confidence scores; absolute class predictions can be obtained with utility functions.
Classifiers follow construct/query pattern; scikit-learn fit/predict pattern can be obtained with utility class.
neighbours.owa_operators moved to utils.owa_operators.
utils.OWAOperator no longer initialised with fixed k, has to be passed to method calls instead.
utils.OWAOperator method calls and functions in utils.np_utils now accept fractional and None k.
Version 0¶
Changelog¶
First release, by Oliver Urs Lenz.
New algorithms¶
Fuzzy Rough Nearest Neighbour Classification with Ordered Weighted Average (OWA) operators