Dataset partitioning strategies
Functions
coarsen_chunks(source[, nchunks]) | Change chunking of the dataset |
xrandom_iterprod(n, *seq) | Generate n random iterprod’s from given sequences |
Classes
CustomPartitioner(splitrule, **kwargs) | Partition a dataset using an arbitrary custom rule. |
ExcludeTargetsCombinationsPartitioner(k, ...) | Exclude combinations for a given partition from other partitions |
FactorialPartitioner(partitioner, **kwargs) | Partitioner for two-level factorial designs |
HalfPartitioner([count, selection_strategy, ...]) | Partition a dataset into two halves of the sample attribute. |
NFoldPartitioner([cvtype]) | Generic N-fold data partitioner. |
NGroupPartitioner([ngroups]) | Partition a dataset into N-groups of the sample attribute. |
Node([space, pass_attr, postproc]) | Common processing object. |
OddEvenPartitioner([usevalues]) | Create odd and even partitions based on a sample attribute. |
Partitioner([count, selection_strategy, ...]) | Generator node to partition a dataset. |
deprecated([extra]) | Decorator to mark a function or class as deprecated. |
iterprod | alias of product |