org.apache.ignite.ml.knn.regression

Class KNNRegressionModel

java.lang.Object

org.apache.ignite.ml.knn.NNClassificationModel

org.apache.ignite.ml.knn.classification.KNNClassificationModel

org.apache.ignite.ml.knn.regression.KNNRegressionModel

All Implemented Interfaces:

Serializable, Function<Vector,Double>, Exportable<KNNModelFormat>, IgniteFunction<Vector,Double>, Model<Vector,Double>

public class KNNRegressionModel
extends KNNClassificationModel

This class provides kNN Multiple Linear Regression or Locally [weighted] regression (Simple and Weighted versions).

This is an instance-based learning method.

• Local means using nearby points (i.e. a nearest neighbors approach).
• Weighted means we value points based upon how far away they are.
• Regression means approximating a function.

See Also:

Serialized Form

Field Summary

Fields inherited from class org.apache.ignite.ml.knn.NNClassificationModel

distanceMeasure, k, stgy

Constructor Summary

Constructors

Constructor and Description
KNNRegressionModel(Dataset<EmptyContext,LabeledVectorSet<Double,LabeledVector>> dataset) Builds the model via prepared dataset.

Method Summary

Modifier and Type	Method and Description
Double	apply(Vector v)
String	toString()
String	toString(boolean pretty)

Methods inherited from class org.apache.ignite.ml.knn.classification.KNNClassificationModel

copyStateFrom, findKNearestNeighbors, saveModel

Methods inherited from class org.apache.ignite.ml.knn.NNClassificationModel

buildLabeledDatasetOnListOfVectors, copyParametersFrom, equals, getClassVoteForVector, getClassWithMaxVotes, getDistanceMeasure, getDistances, getKClosestVectors, hashCode, putDistanceIdxPair, withDistanceMeasure, withK, withStrategy

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.ignite.ml.Model

combine

Methods inherited from interface java.util.function.Function

andThen, compose, identity

Constructor Detail

KNNRegressionModel

public KNNRegressionModel(Dataset<EmptyContext,LabeledVectorSet<Double,LabeledVector>> dataset)

Builds the model via prepared dataset.

Parameters:

dataset - Specially prepared object to run algorithm over it.

Method Detail

apply

public Double apply(Vector v)

Specified by:

apply in interface Function<Vector,Double>

Overrides:

apply in class KNNClassificationModel

toString

public String toString()

Overrides:

toString in class NNClassificationModel

toString

public String toString(boolean pretty)

Specified by:

toString in interface Model<Vector,Double>

Overrides:

toString in class NNClassificationModel

Parameters:

pretty - Use pretty mode.