Uses of Class
eu.h2020.helios_social.modules.socialgraphmining.GNN.GNNMiner

Packages that use GNNMiner

Package	Description
eu.h2020.helios_social.modules.socialgraphmining.GNN

Uses of GNNMiner in eu.h2020.helios_social.modules.socialgraphmining.GNN

Methods in eu.h2020.helios_social.modules.socialgraphmining.GNN that return GNNMiner

Modifier and Type	Method	Description
GNNMiner	CentralizedGNNMiner.getBaseMiner()
GNNMiner	GNNMiner.setDeniability(double plausibleDeniability, double differentialPrivacy)	Enables plausible deniability and differential privacy handling by permuting the ego and its alter's parameters with a random noise proportional to a given constant and their norm.
GNNMiner	GNNMiner.setEdgePointsLearningMultiplier(double incomming, double outgoing)
GNNMiner	GNNMiner.setEmbeddingExchangeProtocol(EmbeddingExchangeProtocol embeddingExchangeProtocol)
GNNMiner	GNNMiner.setLearningRate(double learningRate)	The learning rate (default is 1) from which GNNMiner training starts.
GNNMiner	GNNMiner.setLearningRateDegradation(double learningRateDegradation)	Performs a fixed degradation of the learning rate over training epochs by multiplying the latter with a given factor (default is 0.95) after each epoch.
GNNMiner	GNNMiner.setMaxTrainingEpoch(int maxEpoch)	Limits the number of training epochs (default is 1000) over which to train the GNNMiner.
GNNMiner	GNNMiner.setMinTrainingRelativeLoss(double convergenceRelativeLoss)	When the GNNMiner is being trained, training stops at epochs where abs(previous epoch loss - this epoch loss) < convergenceRelativeLoss*(this epoch loss) where losses are weighted cross entropy ones.
GNNMiner	GNNMiner.setRegularizationAbsorbsion(double regularizationAbsorbsion)	Multiplies regularization tensors with this value before setting them as regularization; value of 1 (default) produces regularization of calculated alter embeddings towards the embeddings calculated on alter devices.
GNNMiner	GNNMiner.setRegularizationWeight(double regularizationWeight)	The regularization weight (default 0.1) to apply during training of the GNNMiner.
GNNMiner	GNNMiner.setSpectralAlignment(boolean enableSpectralAlignment)	Faster convergence to more robust embeddings of evolving user preferences by trying to align the dimensions of received embeddings towards with their locally understood spectral representation (default is false).
GNNMiner	GNNMiner.setTrainingExampleDegradation(double trainingExampleDegradation)	Degrades example weights each time a new one is generated through SocialGraphMiner.newInteraction(eu.h2020.helios_social.core.contextualegonetwork.Interaction, java.lang.String, eu.h2020.helios_social.modules.socialgraphmining.SocialGraphMiner.InteractionType) by calling ContextTrainingExampleData.degrade(double, double) to multiply previous weights with the given degradation factor (default is 0.5).
GNNMiner	GNNMiner.setTrainingExamplePropagation(boolean enableTrainingExamplePropagation)	Sets whether to propagate training examples to communicating devices (this behavior is de-activeated by default).
GNNMiner	GNNMiner.setTrainingExampleRemovalThreshold(double trainingExampleRemovalThreshold)	Sets the threshold weight at which old training examples are removed (default is 0.1).