ai.libs.jaicore.ml.dyadranking.algorithm

Interface IPLNetDyadRankerConfiguration

All Superinterfaces:

org.aeonbits.owner.Config, IPredictiveModelConfiguration, org.aeonbits.owner.Mutable, java.io.Serializable

@Config.Sources(value="file:conf/plNet/plnet.properties")
public interface IPLNetDyadRankerConfiguration
extends IPredictiveModelConfiguration

Nested Class Summary

Nested classes/interfaces inherited from interface org.aeonbits.owner.Config

org.aeonbits.owner.Config.ConverterClass, org.aeonbits.owner.Config.DecryptorClass, org.aeonbits.owner.Config.DefaultValue, org.aeonbits.owner.Config.DisableableFeature, org.aeonbits.owner.Config.DisableFeature, org.aeonbits.owner.Config.EncryptedValue, org.aeonbits.owner.Config.HotReload, org.aeonbits.owner.Config.HotReloadType, org.aeonbits.owner.Config.Key, org.aeonbits.owner.Config.LoadPolicy, org.aeonbits.owner.Config.LoadType, org.aeonbits.owner.Config.PreprocessorClasses, org.aeonbits.owner.Config.Separator, org.aeonbits.owner.Config.Sources, org.aeonbits.owner.Config.TokenizerClass

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	K_ACTIVATION_FUNCTION The activation function for the hidden layers.
static java.lang.String	K_EARLY_STOPPING_INTERVAL How often (in epochs) the validation error should be checked for early stopping.
static java.lang.String	K_EARLY_STOPPING_PATIENCE For how many epochs early stopping should wait until training is stopped if no improvement in the validation error is observed.
static java.lang.String	K_EARLY_STOPPING_RETRAIN Whether to retrain on the full training data after early stopping, using the same number of epochs the model was trained for before early stopping occured.
static java.lang.String	K_EARLY_STOPPING_TRAIN_RATIO The ratio of data used for training in early stopping. 1 - this ratio is used for testing.
static java.lang.String	K_MAX_EPOCHS The maximum number of epochs to be used during training, i.e. how many times the training algorithm should iterate through the entire training data set.
static java.lang.String	K_MINI_BATCH_SIZE The size of mini batches used during training.
static java.lang.String	K_PLNET_HIDDEN_NODES List of integers describing the architecture of the hidden layers.
static java.lang.String	K_PLNET_LEARNINGRATE The learning rate for the gradient updater.
static java.lang.String	K_PLNET_SEED The random seed to use.

Method Summary

Modifier and Type	Method and Description
java.lang.String	plNetActivationFunction()
int	plNetEarlyStoppingInterval()
int	plNetEarlyStoppingPatience()
boolean	plNetEarlyStoppingRetrain()
double	plNetEarlyStoppingTrainRatio()
java.util.List<java.lang.Integer>	plNetHiddenNodes()
double	plNetLearningRate()
int	plNetMaxEpochs()
int	plNetMiniBatchSize()
int	plNetSeed()

Methods inherited from interface org.aeonbits.owner.Mutable

addPropertyChangeListener, addPropertyChangeListener, clear, load, load, removeProperty, removePropertyChangeListener, setProperty

Field Detail

K_PLNET_LEARNINGRATE

static final java.lang.String K_PLNET_LEARNINGRATE

The learning rate for the gradient updater.

See Also:

Constant Field Values

K_PLNET_HIDDEN_NODES

static final java.lang.String K_PLNET_HIDDEN_NODES

List of integers describing the architecture of the hidden layers. The i-th element represents the number of units in the i-th hidden layer.

See Also:

Constant Field Values

K_PLNET_SEED

static final java.lang.String K_PLNET_SEED

The random seed to use.

See Also:

Constant Field Values

K_ACTIVATION_FUNCTION

static final java.lang.String K_ACTIVATION_FUNCTION

The activation function for the hidden layers. For a list of supported functions, see https://deeplearning4j.org/docs/latest/deeplearning4j-cheat-sheet#config-afn

See Also:

Constant Field Values

K_MAX_EPOCHS

static final java.lang.String K_MAX_EPOCHS

The maximum number of epochs to be used during training, i.e. how many times the training algorithm should iterate through the entire training data set. Set to 0 for no limit apart from early stopping.

See Also:

Constant Field Values

K_MINI_BATCH_SIZE

static final java.lang.String K_MINI_BATCH_SIZE

The size of mini batches used during training.

See Also:

Constant Field Values

K_EARLY_STOPPING_INTERVAL

static final java.lang.String K_EARLY_STOPPING_INTERVAL

How often (in epochs) the validation error should be checked for early stopping.

See Also:

Constant Field Values

K_EARLY_STOPPING_PATIENCE

static final java.lang.String K_EARLY_STOPPING_PATIENCE

For how many epochs early stopping should wait until training is stopped if no improvement in the validation error is observed.

See Also:

Constant Field Values

K_EARLY_STOPPING_TRAIN_RATIO

static final java.lang.String K_EARLY_STOPPING_TRAIN_RATIO

The ratio of data used for training in early stopping. 1 - this ratio is used for testing.

See Also:

Constant Field Values

K_EARLY_STOPPING_RETRAIN

static final java.lang.String K_EARLY_STOPPING_RETRAIN

Whether to retrain on the full training data after early stopping, using the same number of epochs the model was trained for before early stopping occured.

See Also:

Constant Field Values

Method Detail

plNetLearningRate

@Config.Key(value="plnet.learningrate")
 @Config.DefaultValue(value="0.1")
double plNetLearningRate()

plNetHiddenNodes

@Config.Key(value="plnet.hidden.nodes")
 @Config.DefaultValue(value="8")
java.util.List<java.lang.Integer> plNetHiddenNodes()

plNetSeed

@Config.Key(value="plnet.seed")
 @Config.DefaultValue(value="42")
int plNetSeed()

plNetActivationFunction

@Config.Key(value="plnet.hidden.activation.function")
 @Config.DefaultValue(value="SIGMOID")
java.lang.String plNetActivationFunction()

plNetMaxEpochs

@Config.Key(value="plnet.epochs")
 @Config.DefaultValue(value="25")
int plNetMaxEpochs()

plNetMiniBatchSize

@Config.Key(value="plnet.minibatch.size")
 @Config.DefaultValue(value="4")
int plNetMiniBatchSize()

plNetEarlyStoppingInterval

@Config.Key(value="plnet.early.stopping.interval")
 @Config.DefaultValue(value="1")
int plNetEarlyStoppingInterval()

plNetEarlyStoppingPatience

@Config.Key(value="plnet.early.stopping.patience")
 @Config.DefaultValue(value="10")
int plNetEarlyStoppingPatience()

plNetEarlyStoppingTrainRatio

@Config.Key(value="plnet.early.stopping.train.ratio")
 @Config.DefaultValue(value="0.8")
double plNetEarlyStoppingTrainRatio()

plNetEarlyStoppingRetrain

@Config.Key(value="plnet.early.stopping.retrain")
 @Config.DefaultValue(value="true")
boolean plNetEarlyStoppingRetrain()