public class GDBOnTreesLearningStrategy extends GDBLearningStrategy
baseMdlTrainerBuilder, checkConvergenceStgyFactory, cntOfIterations, compositionWeights, envBuilder, externalLbToInternalMapping, loss, meanLbVal, sampleSize, trainerEnvironment
Constructor and Description |
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GDBOnTreesLearningStrategy(boolean useIdx)
Create an instance of learning strategy.
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Modifier and Type | Method and Description |
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<K,V> List<IgniteModel<Vector,Double>> |
update(GDBTrainer.GDBModel mdlToUpdate,
DatasetBuilder<K,V> datasetBuilder,
Preprocessor<K,V> vectorizer)
Gets state of model in arguments, compare it with training parameters of trainer and if they are fit then trainer
updates model in according to new data and return new model.
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getCompositionWeights, getMeanValue, initLearningState, learnModels, withBaseModelTrainerBuilder, withCheckConvergenceStgyFactory, withCntOfIterations, withCompositionWeights, withDefaultGradStepSize, withEnvironmentBuilder, withExternalLabelToInternal, withLossGradient, withMeanLabelValue, withSampleSize
public GDBOnTreesLearningStrategy(boolean useIdx)
useIdx
- Use index.public <K,V> List<IgniteModel<Vector,Double>> update(GDBTrainer.GDBModel mdlToUpdate, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> vectorizer)
update
in class GDBLearningStrategy
K
- Type of a key in upstream
data.V
- Type of a value in upstream
data.mdlToUpdate
- Learned model.datasetBuilder
- Dataset builder.vectorizer
- Upstream preprocessor.
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024