Class KNNTrainer<T extends Output<T>>

java.lang.Object

org.tribuo.common.nearest.KNNTrainer<T>

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>, Trainer<T>

public class KNNTrainer<T extends Output<T>>
extends Object
implements Trainer<T>

A Trainer for k-nearest neighbour models.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static enum	KNNTrainer.Distance	The available distance functions.

Field Summary

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED

Constructor Summary

Constructors

Constructor	Description
KNNTrainer(int k, KNNTrainer.Distance distance, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend)	Creates a K-NN trainer using the supplied parameters.

Method Summary

Modifier and Type	Method	Description
int	getInvocationCount()	The number of times this trainer instance has had it's train method invoked.
TrainerProvenance	getProvenance()
void	postConfig()	Used by the OLCUT configuration system, and should not be called by external code.
String	toString()
Model<T>	train(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance)	Trains a predictive model using the examples in the given data set.

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.tribuo.Trainer

train

Constructor Details

KNNTrainer

public KNNTrainer(int k,
 KNNTrainer.Distance distance,
 int numThreads,
 EnsembleCombiner<T> combiner,
 KNNModel.Backend backend)

Creates a K-NN trainer using the supplied parameters.

Parameters:

k - The number of nearest neighbours to consider.

distance - The distance function.

numThreads - The number of threads to use.

combiner - The combination function to aggregate the k predictions.

backend - The computational backend.

Method Details

postConfig

public void postConfig()

Used by the OLCUT configuration system, and should not be called by external code.

Specified by:

postConfig in interface com.oracle.labs.mlrg.olcut.config.Configurable

train

public Model<T> train(Dataset<T> examples,
 Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance)

Description copied from interface: Trainer

Trains a predictive model using the examples in the given data set.

Specified by:

train in interface Trainer<T extends Output<T>>

Parameters:

examples - the data set containing the examples.

runProvenance - Training run specific provenance (e.g., fold number).

Returns:

a predictive model that can be used to generate predictions for new examples.

toString

public String toString()

Overrides:

toString in class Object

getInvocationCount

public int getInvocationCount()

Description copied from interface: Trainer

The number of times this trainer instance has had it's train method invoked.

This is used to determine how many times the trainer's RNG has been accessed to ensure replicability in the random number stream.

Specified by:

getInvocationCount in interface Trainer<T extends Output<T>>

Returns:

The number of train invocations.

getProvenance

public TrainerProvenance getProvenance()

Specified by:

getProvenance in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<T extends Output<T>>