public class ExtraTreesTrainer<T extends Output<T>> extends BaggingTrainer<T>
Extremely Randomized Trees are similar to Random Forests, but they add an extra element of randomness in that the split points for features are also chosen randomly. As with Random Forests, feature subsampling is available at each of the nodes. An exception will be thrown if the inner trainer is not a decision tree trainer or if random splitting is turned off.
See:
P. Geurts, D. Ernst, L. Wehenkel. "Extremely Randomized Trees" March 2006. PDF
combiner, innerTrainer, numMembers, rng, seed, trainInvocationCounter
DEFAULT_SEED
Constructor and Description |
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ExtraTreesTrainer(DecisionTreeTrainer<T> trainer,
EnsembleCombiner<T> combiner,
int numMembers)
Constructs an ExtraTreesTrainer with the default seed
Trainer.DEFAULT_SEED . |
ExtraTreesTrainer(DecisionTreeTrainer<T> trainer,
EnsembleCombiner<T> combiner,
int numMembers,
long seed)
Constructs an ExtraTreesTrainer with the supplied seed, trainer, combining function and number of members.
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Modifier and Type | Method and Description |
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protected String |
ensembleName() |
void |
postConfig()
Used by the OLCUT configuration system, and should not be called by external code.
|
String |
toString() |
getInvocationCount, getProvenance, train, trainSingleModel
public ExtraTreesTrainer(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers)
Trainer.DEFAULT_SEED
.
Throws PropertyException
if the trainer is not set to use random split points.
trainer
- The tree trainer.combiner
- The combining function for the ensemble.numMembers
- The number of ensemble members to train.public ExtraTreesTrainer(DecisionTreeTrainer<T> trainer, EnsembleCombiner<T> combiner, int numMembers, long seed)
Throws PropertyException
if the trainer is not set to use random split points.
trainer
- The tree trainer.combiner
- The combining function for the ensemble.numMembers
- The number of ensemble members to train.seed
- The RNG seed.public void postConfig()
BaggingTrainer
postConfig
in interface com.oracle.labs.mlrg.olcut.config.Configurable
postConfig
in class BaggingTrainer<T extends Output<T>>
protected String ensembleName()
ensembleName
in class BaggingTrainer<T extends Output<T>>
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