Interface IPLNetDyadRankerConfiguration
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- All Superinterfaces:
org.aeonbits.owner.Config,org.aeonbits.owner.Mutable,java.io.Serializable
@Sources("file:conf/plNet/plnet.properties") public interface IPLNetDyadRankerConfiguration extends org.aeonbits.owner.Mutable
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Nested Class Summary
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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
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Field Summary
Fields Modifier and Type Field Description static java.lang.StringK_ACTIVATION_FUNCTIONThe activation function for the hidden layers.static java.lang.StringK_EARLY_STOPPING_INTERVALHow often (in epochs) the validation error should be checked for early stopping.static java.lang.StringK_EARLY_STOPPING_PATIENCEFor how many epochs early stopping should wait until training is stopped if no improvement in the validation error is observed.static java.lang.StringK_EARLY_STOPPING_RETRAINWhether 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.StringK_EARLY_STOPPING_TRAIN_RATIOThe ratio of data used for training in early stopping. 1 - this ratio is used for testing.static java.lang.StringK_MAX_EPOCHSThe 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.StringK_MINI_BATCH_SIZEThe size of mini batches used during training.static java.lang.StringK_PLNET_HIDDEN_NODESList of integers describing the architecture of the hidden layers.static java.lang.StringK_PLNET_LEARNINGRATEThe learning rate for the gradient updater.static java.lang.StringK_PLNET_SEEDThe random seed to use.
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description java.lang.StringplNetActivationFunction()intplNetEarlyStoppingInterval()intplNetEarlyStoppingPatience()booleanplNetEarlyStoppingRetrain()doubleplNetEarlyStoppingTrainRatio()java.util.List<java.lang.Integer>plNetHiddenNodes()doubleplNetLearningRate()intplNetMaxEpochs()intplNetMiniBatchSize()intplNetSeed()
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Field Detail
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K_PLNET_LEARNINGRATE
static final java.lang.String K_PLNET_LEARNINGRATE
The learning rate for the gradient updater.- See Also:
- Constant Field Values
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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
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K_PLNET_SEED
static final java.lang.String K_PLNET_SEED
The random seed to use.- See Also:
- Constant Field Values
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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
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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
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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
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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
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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
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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
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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
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Method Detail
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plNetLearningRate
@Key("plnet.learningrate") @DefaultValue("0.1") double plNetLearningRate()
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plNetHiddenNodes
@Key("plnet.hidden.nodes") @DefaultValue("8") java.util.List<java.lang.Integer> plNetHiddenNodes()
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plNetSeed
@Key("plnet.seed") @DefaultValue("42") int plNetSeed()
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plNetActivationFunction
@Key("plnet.hidden.activation.function") @DefaultValue("SIGMOID") java.lang.String plNetActivationFunction()
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plNetMaxEpochs
@Key("plnet.epochs") @DefaultValue("25") int plNetMaxEpochs()
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plNetMiniBatchSize
@Key("plnet.minibatch.size") @DefaultValue("4") int plNetMiniBatchSize()
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plNetEarlyStoppingInterval
@Key("plnet.early.stopping.interval") @DefaultValue("1") int plNetEarlyStoppingInterval()
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plNetEarlyStoppingPatience
@Key("plnet.early.stopping.patience") @DefaultValue("10") int plNetEarlyStoppingPatience()
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plNetEarlyStoppingTrainRatio
@Key("plnet.early.stopping.train.ratio") @DefaultValue("0.8") double plNetEarlyStoppingTrainRatio()
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plNetEarlyStoppingRetrain
@Key("plnet.early.stopping.retrain") @DefaultValue("true") boolean plNetEarlyStoppingRetrain()
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