usevalues : bool
If True the values of the attribute used for partitioning will be
used to determine odd and even samples. If False odd and even
chunks are defined by the order of attribute values, i.e. first
unique attribute is odd, second is even, despite the
corresponding values might indicate the opposite (e.g. in case
of [2,3].
enable_ca : None or list of str
Names of the conditional attributes which should be enabled in addition
to the default ones
disable_ca : None or list of str
Names of the conditional attributes which should be disabled
count : None or int
Desired number of splits to be output. It is limited by the
number of splits possible for a given splitter
(e.g. OddEvenSplitter can have only up to 2 splits). If None,
all splits are output (default).
selection_strategy : str
If count is not None, possible strategies are possible:
‘first’: First count splits are chosen;
‘random’: Random (without replacement) count splits are chosen;
‘equidistant’: Splits which are equidistant from each other.
attr : str
Sample attribute used to determine splits.
space : str
Name of the to be created sample attribute defining the partitions.
In addition, a dataset attribute named ‘space_set’ will be added
to each output dataset, indicating the number of the partition set
it corresponds to.
postproc : Node instance, optional
Node to perform post-processing of results. This node is applied
in __call__() to perform a final processing step on the to be
result dataset. If None, nothing is done.
descr : str
Description of the instance
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