org.apache.ignite.ml.trainers

Class DatasetTrainer<M extends Model,L>

java.lang.Object

org.apache.ignite.ml.trainers.DatasetTrainer<M,L>

Type Parameters:

M - Type of a produced model.

L - Type of a label.

Direct Known Subclasses:

BaggingModelTrainer, DecisionTree, GDBTrainer, MultiLabelDatasetTrainer, RandomForestTrainer, SingleLabelDatasetTrainer

public abstract class DatasetTrainer<M extends Model,L>
extends Object

Interface for trainers. Trainer is just a function which produces model from the data.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DatasetTrainer.EmptyDatasetException EmptyDataset exception.

Field Summary

Fields

Modifier and Type	Field and Description
protected LearningEnvironment	environment Learning Environment.

Constructor Summary

Constructors

Constructor and Description
DatasetTrainer()

Method Summary

Modifier and Type	Method and Description
protected abstract boolean	checkState(M mdl)
abstract <K,V> M	fit(DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Trains model based on the specified data.
<K,V> M	fit(Ignite ignite, IgniteCache<K,V> cache, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Trains model based on the specified data.
<K,V> M	fit(Ignite ignite, IgniteCache<K,V> cache, IgniteBiPredicate<K,V> filter, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Trains model based on the specified data.
<K,V> M	fit(Map<K,V> data, IgniteBiPredicate<K,V> filter, int parts, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Trains model based on the specified data.
<K,V> M	fit(Map<K,V> data, int parts, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Trains model based on the specified data.
protected M	getLastTrainedModelOrThrowEmptyDatasetException(M lastTrainedMdl) Used on update phase when given dataset is empty.
void	setEnvironment(LearningEnvironment environment) Sets learning Environment
<K,V> M	update(M mdl, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) 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.
<K,V> M	update(M mdl, Ignite ignite, IgniteCache<K,V> cache, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
<K,V> M	update(M mdl, Ignite ignite, IgniteCache<K,V> cache, IgniteBiPredicate<K,V> filter, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
<K,V> M	update(M mdl, Map<K,V> data, IgniteBiPredicate<K,V> filter, int parts, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
<K,V> M	update(M mdl, Map<K,V> data, int parts, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
protected abstract <K,V> M	updateModel(M mdl, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,L> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.

Methods inherited from class java.lang.Object

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

Field Detail

environment

protected LearningEnvironment environment

Learning Environment.

Constructor Detail

DatasetTrainer

public DatasetTrainer()

Method Detail

fit

public abstract <K,V> M fit(DatasetBuilder<K,V> datasetBuilder,
                            IgniteBiFunction<K,V,Vector> featureExtractor,
                            IgniteBiFunction<K,V,L> lbExtractor)

Trains model based on the specified data.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

datasetBuilder - Dataset builder.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

update

public <K,V> M update(M mdl,
                      DatasetBuilder<K,V> datasetBuilder,
                      IgniteBiFunction<K,V,Vector> featureExtractor,
                      IgniteBiFunction<K,V,L> lbExtractor)

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. In other case trains new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

datasetBuilder - Dataset builder.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

checkState

protected abstract boolean checkState(M mdl)

Parameters:

mdl - Model.

Returns:

true if current critical for training parameters correspond to parameters from last training.

getLastTrainedModelOrThrowEmptyDatasetException

@NotNull
protected M getLastTrainedModelOrThrowEmptyDatasetException(M lastTrainedMdl)

Used on update phase when given dataset is empty. If last trained model exist then method returns it. In other case throws IllegalArgumentException.

Parameters:

lastTrainedMdl - Model.

updateModel

protected abstract <K,V> M updateModel(M mdl,
                                       DatasetBuilder<K,V> datasetBuilder,
                                       IgniteBiFunction<K,V,Vector> featureExtractor,
                                       IgniteBiFunction<K,V,L> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

datasetBuilder - Dataset builder.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

fit

public <K,V> M fit(Ignite ignite,
                   IgniteCache<K,V> cache,
                   IgniteBiFunction<K,V,Vector> featureExtractor,
                   IgniteBiFunction<K,V,L> lbExtractor)

Trains model based on the specified data.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

ignite - Ignite instance.

cache - Ignite cache.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

update

public <K,V> M update(M mdl,
                      Ignite ignite,
                      IgniteCache<K,V> cache,
                      IgniteBiFunction<K,V,Vector> featureExtractor,
                      IgniteBiFunction<K,V,L> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

ignite - Ignite instance.

cache - Ignite cache.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

fit

public <K,V> M fit(Ignite ignite,
                   IgniteCache<K,V> cache,
                   IgniteBiPredicate<K,V> filter,
                   IgniteBiFunction<K,V,Vector> featureExtractor,
                   IgniteBiFunction<K,V,L> lbExtractor)

Trains model based on the specified data.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

ignite - Ignite instance.

cache - Ignite cache.

filter - Filter for upstream data.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

update

public <K,V> M update(M mdl,
                      Ignite ignite,
                      IgniteCache<K,V> cache,
                      IgniteBiPredicate<K,V> filter,
                      IgniteBiFunction<K,V,Vector> featureExtractor,
                      IgniteBiFunction<K,V,L> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

ignite - Ignite instance.

cache - Ignite cache.

filter - Filter for upstream data.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

fit

public <K,V> M fit(Map<K,V> data,
                   int parts,
                   IgniteBiFunction<K,V,Vector> featureExtractor,
                   IgniteBiFunction<K,V,L> lbExtractor)

Trains model based on the specified data.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

data - Data.

parts - Number of partitions.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

update

public <K,V> M update(M mdl,
                      Map<K,V> data,
                      int parts,
                      IgniteBiFunction<K,V,Vector> featureExtractor,
                      IgniteBiFunction<K,V,L> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

data - Data.

parts - Number of partitions.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

fit

public <K,V> M fit(Map<K,V> data,
                   IgniteBiPredicate<K,V> filter,
                   int parts,
                   IgniteBiFunction<K,V,Vector> featureExtractor,
                   IgniteBiFunction<K,V,L> lbExtractor)

Trains model based on the specified data.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

data - Data.

filter - Filter for upstream data.

parts - Number of partitions.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

update

public <K,V> M update(M mdl,
                      Map<K,V> data,
                      IgniteBiPredicate<K,V> filter,
                      int parts,
                      IgniteBiFunction<K,V,Vector> featureExtractor,
                      IgniteBiFunction<K,V,L> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

data - Data.

filter - Filter for upstream data.

parts - Number of partitions.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

setEnvironment

public void setEnvironment(LearningEnvironment environment)

Sets learning Environment

Parameters:

environment - Environment.