K
- Type of a key in upstream data.O
- Type of an object of recommendation.S
- Type of a subject of recommendation.Z
- Type of object-subject pair.public class RecommendationDatasetDataBuilder<K,O extends Serializable,S extends Serializable,Z extends ObjectSubjectRatingTriplet<O,S>> extends Object implements PartitionDataBuilder<K,Z,EmptyContext,RecommendationDatasetData<O,S>>
data
builder that makes SimpleDatasetData
.Constructor and Description |
---|
RecommendationDatasetDataBuilder() |
Modifier and Type | Method and Description |
---|---|
RecommendationDatasetData<O,S> |
build(LearningEnvironment env,
Iterator<UpstreamEntry<K,Z>> upstreamData,
long upstreamDataSize,
EmptyContext ctx)
Builds a new partition
data from a partition upstream data and partition context . |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
andThen, build
public RecommendationDatasetData<O,S> build(LearningEnvironment env, Iterator<UpstreamEntry<K,Z>> upstreamData, long upstreamDataSize, EmptyContext ctx)
data
from a partition upstream
data and partition context
.
Important: there is no guarantee that there will be no more than one UpstreamEntry with given key,
UpstreamEntry should be thought rather as a container saving all data from upstream, but omitting uniqueness
constraint. This constraint is omitted to allow upstream data transformers in DatasetBuilder
replicating
entries. For example it can be useful for bootstrapping.build
in interface PartitionDataBuilder<K,Z extends ObjectSubjectRatingTriplet<O,S>,EmptyContext,RecommendationDatasetData<O extends Serializable,S extends Serializable>>
env
- Learning environment.upstreamData
- Partition upstream
data.upstreamDataSize
- Partition upstream
data size.ctx
- Partition context
.data
.
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024