Package | Description |
---|---|
org.apache.ignite.ml.composition.combinators.sequential |
Contains sequential combinators of trainers and models.
|
org.apache.ignite.ml.trainers |
Contains model trainers.
|
Modifier and Type | Method and Description |
---|---|
static <I,O,L> TrainersSequentialComposition<I,O,O,L> |
TrainersSequentialComposition.ofSame(DatasetTrainer<? extends IgniteModel<I,O>,L> tr,
IgniteBiFunction<Integer,? super IgniteModel<I,O>,IgniteFunction<LabeledVector<L>,LabeledVector<L>>> datasetMapping,
IgniteBiPredicate<Integer,IgniteModel<I,O>> shouldStop,
IgniteFunction<O,I> out2In)
Construct sequential composition of same trainers.
|
Modifier and Type | Method and Description |
---|---|
<O1,M1 extends IgniteModel<O,O1>> |
AdaptableDatasetTrainer.andThen(DatasetTrainer<M1,L> tr,
IgniteFunction<AdaptableDatasetModel<I,O,IW,OW,M>,IgniteFunction<LabeledVector<L>,LabeledVector<L>>> datasetMappingProducer)
Create a
TrainersSequentialComposition of whis trainer and specified trainer. |
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024