deepnetts.automl

Class HyperParameterSearch

java.lang.Object

deepnetts.automl.HyperParameterSearch

public class HyperParameterSearch
extends Object

The core automl class that performs automated model building and evaluation with specified parameters.

Field Summary

Fields

Modifier and Type	Field and Description
static String	DIVIDE_AND_CONQUER
static String	GRID
static String	RANDOM

Constructor Summary

Constructors

Constructor and Description
HyperParameterSearch()

Method Summary

Modifier and Type	Method and Description
HyperParameterSearch	evaluator(javax.visrec.ml.eval.Evaluator<NeuralNetwork,javax.visrec.ml.data.DataSet<? extends MLDataItem>> evaluator)
javax.visrec.ml.eval.Evaluator<NeuralNetwork,javax.visrec.ml.data.DataSet<? extends MLDataItem>>	getEvaluator()
NeuralNetwork	getNetwork()
Parameters	getParameters()
List<TrainingResult>	getResults()
List<Parameters.ParameterCombination>	getSearchSpace()
javax.visrec.ml.data.DataSet<?>	getTrainingSet()
HyperParameterSearch	networkFactory(NetworkFactory<?> networkFactory)
<T> HyperParameterSearch	param(String name, List<T> values)
<T> HyperParameterSearch	param(String name, Range<T> range, String searchStrategy)
<T> HyperParameterSearch	param(String name, T value)
HyperParameterSearch	randomSeed(long randomSeed)
void	run()
HyperParameterSearch	testSet(javax.visrec.ml.data.DataSet testSet)
HyperParameterSearch	trainingListener(TrainingListener trainingListener)
HyperParameterSearch	trainingSet(javax.visrec.ml.data.DataSet trainingSet)

Methods inherited from class java.lang.Object

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

Field Detail

GRID

public static final String GRID

See Also:

Constant Field Values

RANDOM

public static final String RANDOM

See Also:

Constant Field Values

DIVIDE_AND_CONQUER

public static final String DIVIDE_AND_CONQUER

See Also:

Constant Field Values

Constructor Detail

HyperParameterSearch

public HyperParameterSearch()

Method Detail

trainingSet

public HyperParameterSearch trainingSet(javax.visrec.ml.data.DataSet trainingSet)

testSet

public HyperParameterSearch testSet(javax.visrec.ml.data.DataSet testSet)

evaluator

public HyperParameterSearch evaluator(javax.visrec.ml.eval.Evaluator<NeuralNetwork,javax.visrec.ml.data.DataSet<? extends MLDataItem>> evaluator)

trainingListener

public HyperParameterSearch trainingListener(TrainingListener trainingListener)

param

public <T> HyperParameterSearch param(String name,
                                      T value)

param

public <T> HyperParameterSearch param(String name,
                                      List<T> values)

param

public <T> HyperParameterSearch param(String name,
                                      Range<T> range,
                                      String searchStrategy)

getParameters

public Parameters getParameters()

getNetwork

public final NeuralNetwork getNetwork()

getTrainingSet

public final javax.visrec.ml.data.DataSet<?> getTrainingSet()

getEvaluator

public final javax.visrec.ml.eval.Evaluator<NeuralNetwork,javax.visrec.ml.data.DataSet<? extends MLDataItem>> getEvaluator()

run

public void run()

getSearchSpace

public List<Parameters.ParameterCombination> getSearchSpace()

getResults

public List<TrainingResult> getResults()

randomSeed

public HyperParameterSearch randomSeed(long randomSeed)

networkFactory

public HyperParameterSearch networkFactory(NetworkFactory<?> networkFactory)