0.8
Version 0.8
-
New The
skcriteria.cmp
package utilities to compare rankings. -
New The new package
skcriteria.datasets
include two datasets (one a
toy and one real) to quickly start your experiments. -
New DecisionMatrix now can be sliced with a syntax similar of the
pandas.DataFrame.-
dm["c0"]
cut the$c0$ criteria. -
dm[["c0", "c2"]
cut the criteria$c0$ and$c2$ . -
dm.loc["a0"]
cut the alternative$a0$ . -
dm.loc[["a0", "a1"]]
cut the alternatives$a0$ and$a1$ . -
dm.iloc[0:3]
cuts from the first to the third alternative.
-
-
New imputation methods for replacing missing data with substituted
values. These methods are in the moduleskcriteria.preprocessing.impute
. -
New results object now has a
to_series
method. -
Changed Behaviour: The ranks and kernels
equals
are now called
values_equals
. The newaequals
support tolerances to compare
numpy arrays internally stored inextra_
, and theequals
method is
equivalent toaequals(rtol=0, atol=0)
. -
We detected a bad behavior in ELECTRE2, so we decided to launch a
FutureWarning
when the
class is instantiated. In the version after 0.8, a new implementation of ELECTRE2 will be
provided. -
Multiple
__repr__
was improved to folow the
Python recomendation -
Critic
weighter was renamed toCRITIC
(all capitals) to be consistent
with the literature. The old class is still there but is deprecated. -
All the functions and classes of
skcriteria.preprocessing.distance
was
moved toskcriteria.preprocessing.scalers
. -
The
StdWeighter
now uses the sample standar-deviation.
From the numerical point of view, this does not generate any change,
since the deviations are scaled by the sum. Computationally speaking there
may be some difference from the ~5th decimal digit onwards. -
Two method of the
Objective
enum was deprecated and replaced:-
Objective.construct_from_alias()
->
Objective.from_alias()
(classmethod) -
Objective.to_string()
->
Objective.to_symbol()'
The deprecated methods will be removed in version 1.0.
-
-
Add a dominance plot
DecisionMatrix.plot.dominance()
. -
WeightedSumModel
raises aValueError
when some value$< 0$ . -
Moved internal modules
-
skcriteria.core.methods.SKCTransformerABC
->
skcriteria.preprocessing.SKCTransformerABC
-
skcriteria.core.methods.SKCMatrixAndWeightTransformerABC
->
skcriteria.preprocessing.SKCMatrixAndWeightTransformerABC
-