org.encog.ensemble
Modifier and Type | Class and Description |
---|---|
class |
Ensemble.NotPossibleInThisMethod |
Modifier and Type | Field and Description |
---|---|
protected EnsembleAggregator |
aggregator |
protected MLDataSet |
aggregatorDataSet |
protected EnsembleDataSetFactory |
dataSetFactory |
protected ArrayList<EnsembleML> |
members |
protected EnsembleMLMethodFactory |
mlFactory |
protected EnsembleTrainFactory |
trainFactory |
Constructor and Description |
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Ensemble() |
Modifier and Type | Method and Description |
---|---|
void |
addMember(EnsembleML newMember)
Add a member to the ensemble
|
MLData |
compute(MLData input)
Compute the output for a specific input
|
EnsembleAggregator |
getAggregator() |
EnsembleML |
getMember(int memberNumber)
Extract a specific MLMethod
|
abstract EnsembleTypes.ProblemType |
getProblemType()
Return what type of problem this Ensemble is solving
|
MLDataSet |
getTrainingSet(int setNumber)
Extract a specific training set from the Ensemble
|
abstract void |
initMembers()
Initialise ensemble components
|
void |
initMembersBySplits(int splits) |
void |
setAggregator(EnsembleAggregator aggregator)
Sets the ensemble aggregation method
|
void |
setTrainingData(MLDataSet data)
Set which training data to base the training on
|
void |
setTrainingDataFactory(EnsembleDataSetFactory dataSetFactory)
Set which dataSetFactory to use to create the correct tranining sets
|
void |
setTrainingMethod(EnsembleTrainFactory newTrainFactory)
Set the training method to use for this ensemble
|
void |
train(double targetError,
double selectionError,
EnsembleDataSet testset)
Train the ensemble to a target accuracy
|
void |
train(double targetError,
double selectionError,
EnsembleDataSet testset,
boolean verbose)
Train the ensemble to a target accuracy
|
protected EnsembleDataSetFactory dataSetFactory
protected EnsembleTrainFactory trainFactory
protected EnsembleAggregator aggregator
protected ArrayList<EnsembleML> members
protected EnsembleMLMethodFactory mlFactory
protected MLDataSet aggregatorDataSet
public abstract void initMembers()
public void initMembersBySplits(int splits)
public void setTrainingMethod(EnsembleTrainFactory newTrainFactory)
newTrainFactory
- The training factory.public void setTrainingData(MLDataSet data)
data
- The training data.public void setTrainingDataFactory(EnsembleDataSetFactory dataSetFactory)
dataSetFactory
- The data set factory.public void train(double targetError, double selectionError, EnsembleDataSet testset, boolean verbose)
targetError
- The target error.selectionError
- The selection error.testset
- The test set.verbose
- Verbose mode?public void train(double targetError, double selectionError, EnsembleDataSet testset)
targetError
- The target error.selectionError
- The selection error.testset
- The test set.public MLDataSet getTrainingSet(int setNumber)
setNumber
- public EnsembleML getMember(int memberNumber)
memberNumber
- public void addMember(EnsembleML newMember) throws Ensemble.NotPossibleInThisMethod
newMember
- Ensemble.NotPossibleInThisMethod
public MLData compute(MLData input)
input
- public EnsembleAggregator getAggregator()
public void setAggregator(EnsembleAggregator aggregator)
aggregator
- public abstract EnsembleTypes.ProblemType getProblemType()
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