org.apache.ignite.ml.knn

Class KNNPartitionDataBuilder<K,V>

java.lang.Object

org.apache.ignite.ml.knn.KNNPartitionDataBuilder<K,V>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

All Implemented Interfaces:

Serializable, PartitionDataBuilder<K,V,EmptyContext,SpatialIndex<Double>>

public class KNNPartitionDataBuilder<K,V>
extends Object
implements PartitionDataBuilder<K,V,EmptyContext,SpatialIndex<Double>>

Partition data builder for KNN algorithms based on SpatialIndex.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
KNNPartitionDataBuilder(Preprocessor<K,V> preprocessor, SpatialIndexType spatialIdxType, DistanceMeasure distanceMeasure) Constructs a new instance of KNN partition data builder.

Method Summary

Modifier and Type	Method and Description
SpatialIndex<Double>	build(LearningEnvironment env, Iterator<UpstreamEntry<K,V>> upstreamData, long upstreamDataSize, EmptyContext ctx) Builds a new partition data from a partition upstream data and partition context.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.ignite.ml.dataset.PartitionDataBuilder

andThen, build

Constructor Detail

KNNPartitionDataBuilder

public KNNPartitionDataBuilder(Preprocessor<K,V> preprocessor,
                               SpatialIndexType spatialIdxType,
                               DistanceMeasure distanceMeasure)

Constructs a new instance of KNN partition data builder.

Parameters:

preprocessor - Data preprocessor.

spatialIdxType - Spatial index type.

distanceMeasure - Distance measure.

Method Detail

build

public SpatialIndex<Double> build(LearningEnvironment env,
                                  Iterator<UpstreamEntry<K,V>> upstreamData,
                                  long upstreamDataSize,
                                  EmptyContext ctx)

Builds a new partition 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.

Specified by:

build in interface PartitionDataBuilder<K,V,EmptyContext,SpatialIndex<Double>>

Parameters:

env - Learning environment.

upstreamData - Partition upstream data.

upstreamDataSize - Partition upstream data size.

ctx - Partition context.

Returns:

Partition data.