Index (aika 0.19 API)

A B C D E F G H I K L M N O P Q R S T U V W Z

A

AbstractNode<P extends Provider<? extends AbstractNode>,A extends NodeActivation> - Class in network.aika
AbstractNode() - Constructor for class network.aika.AbstractNode
accumulatedWeight - Variable in class network.aika.neuron.activation.SearchNode
acquireReadLock() - Method in class network.aika.ReadWriteLock
acquireWriteLock() - Method in class network.aika.ReadWriteLock
activatedNeurons - Variable in class network.aika.Document
activatedNodes - Variable in class network.aika.Document
Activation - Class in network.aika.neuron.activation: The Activation class is the most central class in Aika.
Activation(int, Document, OrNode) - Constructor for class network.aika.neuron.activation.Activation
Activation(int, Document, Range, OrNode) - Constructor for class network.aika.neuron.activation.Activation
activation - Variable in class network.aika.neuron.activation.Candidate
Activation.Builder - Class in network.aika.neuron.activation
Activation.Link - Class in network.aika.neuron.activation: The SynapseActivation mirror the synapse link in the network of activations.
Activation.Mode - Enum in network.aika.neuron.activation
Activation.Rounds - Class in network.aika.neuron.activation: Since Aika is a recurrent neural network, it is necessary to compute several rounds of activation values.
Activation.State - Class in network.aika.neuron.activation: A State object contains the activation value of an activation object that belongs to a neuron.
Activation.StateChange - Class in network.aika.neuron.activation: The StateChange class is used to store the state change of an activation that occurs in each node of the binary search tree.
ACTIVATION_ID_COMP - Static variable in class network.aika.neuron.activation.Activation
ActivationFunction - Enum in network.aika
activationFunction - Variable in class network.aika.neuron.INeuron
activationIdCounter - Variable in class network.aika.Document
activations - Variable in class network.aika.lattice.Node.ThreadState
activations - Variable in class network.aika.neuron.INeuron.ThreadState
ACTIVATIONS_OUTPUT_COMPARATOR - Static variable in class network.aika.Document
activationsByRangeBegin - Variable in class network.aika.Document
activationsByRangeEnd - Variable in class network.aika.Document
activationsEnd - Variable in class network.aika.neuron.INeuron.ThreadState
activationsToString() - Method in class network.aika.Document
activationsToString(boolean, boolean, boolean) - Method in class network.aika.Document
activeProviders - Variable in class network.aika.Model
ActKey(Range, Node, int) - Constructor for class network.aika.Document.ActKey
ActKey(Range, int) - Constructor for class network.aika.neuron.INeuron.ActKey
add(Node) - Method in class network.aika.Document.Queue
add(Activation) - Method in class network.aika.Document.UpperBoundQueue
add(int, Activation) - Method in class network.aika.Document.ValueQueue
add(Model, INeuron) - Static method in class network.aika.lattice.InputNode
add(Activation) - Method in class network.aika.training.SupervisedTraining.BackPropagationQueue
addActivation(Activation) - Method in class network.aika.lattice.InputNode
addActivation(A) - Method in class network.aika.lattice.Node: Add a new activation to this logic node and further propagate this activation through the network.
added - Variable in class network.aika.lattice.Node.ThreadState
addedActivations - Variable in class network.aika.Document
addedNodeActivations - Variable in class network.aika.Document
addedNodes - Variable in class network.aika.Document
addInMemoryInputSynapse(Synapse) - Method in class network.aika.neuron.Neuron
addInMemoryOutputSynapse(Synapse) - Method in class network.aika.neuron.Neuron
addInput(int[], int, Node, boolean) - Method in class network.aika.lattice.OrNode
addInput(Document, Activation.Builder) - Method in class network.aika.neuron.INeuron: Propagate an input activation into the network.
addInput(Document, int, int) - Method in class network.aika.neuron.Neuron: Propagate an input activation into the network.
addInput(Document, Range) - Method in class network.aika.neuron.Neuron: Propagate an input activation into the network.
addInput(Document, Activation.Builder) - Method in class network.aika.neuron.Neuron: Propagate an input activation into the network.
addInputActivation(OrNode.OrEntry, NodeActivation) - Method in class network.aika.lattice.OrNode
addInstanceRelation(InstanceRelation.Type, int) - Method in class network.aika.neuron.Synapse.Builder
addRangeRelation(Range.Relation, int) - Method in class network.aika.neuron.Synapse.Builder
addRelations(Map<Integer, Relation>) - Method in class network.aika.neuron.Synapse.Builder
addSynapse(Synapse.Builder) - Method in class network.aika.neuron.Neuron
addSynapse(Document, Synapse.Builder) - Method in class network.aika.neuron.Neuron
addSynapseActivation(Linker.Direction, Activation.Link) - Method in class network.aika.neuron.activation.Activation
adjustSelectedNeuronInputs(SearchNode.Decision) - Method in class network.aika.neuron.activation.Activation
ALLOW_WEAK_NEGATIVE_WEIGHTS - Static variable in class network.aika.neuron.INeuron
AndActivation(int, Document, AndNode) - Constructor for class network.aika.lattice.AndNode.AndActivation
andChildren - Variable in class network.aika.lattice.Node
AndNode - Class in network.aika.lattice: The InputNode and the AndNode classes together form a pattern lattice, containing all possible substructures of any given conjunction.
AndNode() - Constructor for class network.aika.lattice.AndNode
AndNode(Model, int, SortedMap<AndNode.Refinement, AndNode.RefValue>) - Constructor for class network.aika.lattice.AndNode
AndNode.AndActivation - Class in network.aika.lattice
AndNode.Link - Class in network.aika.lattice
AndNode.Refinement - Class in network.aika.lattice
AndNode.RefValue - Class in network.aika.lattice
AndNode.RelationsMap - Class in network.aika.lattice
andParents - Variable in class network.aika.lattice.OrNode
append(String) - Method in class network.aika.Document
apply(Activation) - Method in class network.aika.lattice.OrNode
avgState - Variable in class network.aika.neuron.activation.Activation

B

BackPropagationQueue() - Constructor for class network.aika.training.SupervisedTraining.BackPropagationQueue
backpropagtion() - Method in class network.aika.training.SupervisedTraining.BackPropagationQueue
begin - Variable in class network.aika.neuron.activation.Range
BEGIN - Static variable in class network.aika.neuron.activation.Range.Output
begin - Variable in class network.aika.neuron.activation.Range.Output
BEGIN_COMP - Static variable in class network.aika.neuron.activation.Range
BEGIN_COMP - Static variable in class network.aika.neuron.INeuron
BEGIN_EQUALS - Static variable in class network.aika.neuron.activation.Range.Relation
BEGIN_TO_END_EQUALS - Static variable in class network.aika.neuron.activation.Range.Relation
beginToBegin - Variable in class network.aika.neuron.activation.Range.Relation
beginToEnd - Variable in class network.aika.neuron.activation.Range.Relation
bestChildNode - Variable in class network.aika.neuron.activation.Candidate
bias - Variable in class network.aika.neuron.INeuron
bias - Variable in class network.aika.neuron.Synapse
bias - Variable in class network.aika.neuron.Synapse.Builder
biasDelta - Variable in class network.aika.neuron.INeuron
biasDelta - Variable in class network.aika.neuron.Synapse
biasSum - Variable in class network.aika.neuron.INeuron
biasSumDelta - Variable in class network.aika.neuron.INeuron
Builder() - Constructor for class network.aika.neuron.activation.Activation.Builder
Builder() - Constructor for class network.aika.neuron.Synapse.Builder

C

cachedDecision - Variable in class network.aika.neuron.activation.Candidate: The cached decision is used to avoid having to explore the same candidate twice even though nothing that influences this candidate has changed.
cachedSearchNode - Variable in class network.aika.neuron.activation.Candidate: The cached search node is used to avoid having to recompute the activation values and weights that are associated with this search node.
candidate - Variable in class network.aika.neuron.activation.Activation
Candidate - Class in network.aika.neuron.activation
Candidate(Activation, int) - Constructor for class network.aika.neuron.activation.Candidate
candidate - Variable in class network.aika.neuron.activation.SearchNode
CANDIDATE_RELATIONS - Static variable in class network.aika.lattice.InputNode
candidateCheck - Variable in class network.aika.training.PatternDiscovery.Config
candidates - Variable in class network.aika.Document
changeBias(double) - Method in class network.aika.neuron.INeuron
changeNumberOfNeuronRefs(int, long, int) - Method in class network.aika.lattice.AndNode
changeNumberOfNeuronRefs(int, long, int) - Method in class network.aika.lattice.Node
changeNumberOfNeuronRefs(int, long, int) - Method in class network.aika.lattice.OrNode
changeState(Activation.Mode) - Method in class network.aika.neuron.activation.SearchNode
charAt(int) - Method in class network.aika.Document
check(NodeActivation, NodeActivation) - Method in interface network.aika.training.PatternDiscovery.CandidateCheck: Check if node is an interesting pattern that might be considered for further processing.
check(AndNode) - Method in interface network.aika.training.PatternDiscovery.PatternCheck
checkDependenciesSatisfied(long) - Method in class network.aika.neuron.activation.Candidate
checkIfDelete(Synapse, boolean) - Method in enum network.aika.training.SynapseEvaluation.DeleteMode
checkSelfReferencing(boolean, int, long) - Method in class network.aika.neuron.activation.Activation
child - Variable in class network.aika.lattice.AndNode.RefValue
child - Variable in class network.aika.lattice.OrNode.OrEntry
cleanup() - Method in class network.aika.lattice.AndNode
cleanup() - Method in class network.aika.lattice.InputNode
cleanup() - Method in class network.aika.lattice.Node
cleanup() - Method in class network.aika.lattice.OrNode
CLEANUP_INTERVAL - Static variable in class network.aika.Document
clearActivations() - Method in class network.aika.Document: Removes the activations of this document from the model again.
clearActivations(Document) - Method in class network.aika.lattice.Node
clearActivations(int) - Method in class network.aika.lattice.Node
clearActivations() - Method in class network.aika.lattice.Node
clearActivations() - Method in class network.aika.neuron.INeuron
clearActivations(Document) - Method in class network.aika.neuron.INeuron
clearActivations(int) - Method in class network.aika.neuron.INeuron
collapseText(String, int) - Static method in class network.aika.Utils
commit() - Method in class network.aika.Document: Updates the model after the training step.
committedInDoc - Variable in class network.aika.neuron.Synapse
compare(Activation.Rounds) - Method in class network.aika.neuron.activation.Activation.Rounds
compare(Range, Range, boolean) - Static method in class network.aika.neuron.activation.Range
compare(Range, Range) - Static method in class network.aika.neuron.activation.Range
compare(int, int) - Method in enum network.aika.neuron.activation.Range.Operator
compare(Range, Range) - Method in class network.aika.neuron.activation.Range.Relation
compareInteger(Integer, Integer) - Static method in class network.aika.Utils
compareNewState(SearchNode) - Method in class network.aika.neuron.activation.SearchNode
compareNullSafe(Integer, Integer) - Static method in class network.aika.Utils
compareTo(Document) - Method in class network.aika.Document
compareTo(AndNode.Refinement) - Method in class network.aika.lattice.AndNode.Refinement
compareTo(AndNode.RelationsMap) - Method in class network.aika.lattice.AndNode.RelationsMap
compareTo(Node) - Method in class network.aika.lattice.Node
compareTo(NodeActivation<T>) - Method in class network.aika.lattice.NodeActivation
compareTo(OrNode.OrEntry) - Method in class network.aika.lattice.OrNode.OrEntry
compareTo(Candidate) - Method in class network.aika.neuron.activation.Candidate
compareTo(Range.Output) - Method in class network.aika.neuron.activation.Range.Output
compareTo(Range.Relation) - Method in class network.aika.neuron.activation.Range.Relation
compareTo(SearchNode) - Method in class network.aika.neuron.activation.SearchNode
compareTo(INeuron) - Method in class network.aika.neuron.INeuron
compareTo(Relation) - Method in class network.aika.neuron.relation.InstanceRelation
compareTo(Relation) - Method in class network.aika.neuron.relation.RangeRelation
compareTo(Synapse.Builder) - Method in class network.aika.neuron.Synapse.Builder
compareTo(Synapse.Key) - Method in class network.aika.neuron.Synapse.Key
compareTo(Provider<?>) - Method in class network.aika.Provider
COMPUTE_SOFT_MAX - Static variable in class network.aika.neuron.activation.SearchNode
computeBackpropagationErrorSignal(Activation) - Method in class network.aika.training.SupervisedTraining
computeBounds() - Method in class network.aika.neuron.activation.Activation
computeOutputErrorSignal(Activation) - Method in class network.aika.training.SupervisedTraining
computeValueAndWeight(int) - Method in class network.aika.neuron.activation.Activation
Config() - Constructor for class network.aika.training.PatternDiscovery.Config
Config() - Constructor for class network.aika.training.SupervisedTraining.Config
CONTAINED_IN - Static variable in class network.aika.neuron.activation.Range.Relation
contains(AndNode.Refinement, AndNode.RefValue) - Method in class network.aika.lattice.AndNode.Refinement
contains(Range) - Method in class network.aika.neuron.activation.Range
CONTAINS - Static variable in class network.aika.neuron.activation.Range.Relation
contains(T[], T, Comparator<T>) - Static method in class network.aika.Utils
convert(int, Document, INeuron, Collection<Synapse>) - Static method in class network.aika.Converter
Converter - Class in network.aika: Converts the synapse weights of a neuron into a boolean logic representation of this neuron.
copy() - Method in class network.aika.neuron.activation.Activation.Rounds
count(NodeActivation) - Method in interface network.aika.training.PatternDiscovery.Counter: Updates the statistics of this node
counter - Variable in class network.aika.training.PatternDiscovery.Config
create(Range.Mapping, Range.Mapping) - Static method in class network.aika.neuron.activation.Range.Output
create(Range.Operator, Range.Operator, Range.Operator, Range.Operator) - Static method in class network.aika.neuron.activation.Range.Relation
create(Range.Operator, Range.Operator) - Static method in class network.aika.neuron.activation.Range.Relation
createdInDoc - Variable in class network.aika.neuron.Synapse
createDocument(String) - Method in class network.aika.Model
createDocument(String, int) - Method in class network.aika.Model
createNeuron() - Method in class network.aika.Model
createNeuron(String) - Method in class network.aika.Model
createNeuron(String, String) - Method in class network.aika.Model
createObject() - Method in interface network.aika.Model.WritableFactory
createOrLookup(Document, Integer, Synapse.Key, Map<Integer, Relation>, DistanceFunction, Neuron, Neuron) - Static method in class network.aika.neuron.Synapse
createV - Variable in class network.aika.Document
currentId - Variable in class network.aika.Model
currentSearchNode - Variable in class network.aika.neuron.activation.Candidate
currentStateChange - Variable in class network.aika.neuron.activation.Activation
currentStateV - Variable in class network.aika.neuron.activation.Activation

D

debugComputed - Variable in class network.aika.neuron.activation.Candidate
debugCounts - Variable in class network.aika.neuron.activation.Candidate
debugDecisionCounts - Variable in class network.aika.neuron.activation.Candidate
decision - Variable in class network.aika.neuron.activation.Activation
defaultThreadId - Variable in class network.aika.Model
deleteMode - Variable in class network.aika.training.SynapseEvaluation.Result
DIRECT - Static variable in class network.aika.Converter
DIRECT - Static variable in class network.aika.neuron.activation.Range.Output
discover(AndNode.AndActivation, PatternDiscovery.Config) - Method in class network.aika.lattice.AndNode
discover(InputNode.InputActivation, PatternDiscovery.Config) - Method in class network.aika.lattice.InputNode
discover(A, PatternDiscovery.Config) - Method in class network.aika.lattice.Node
discover(Activation, PatternDiscovery.Config) - Method in class network.aika.lattice.OrNode
discover(Document, PatternDiscovery.Config) - Static method in class network.aika.training.PatternDiscovery
DistanceFunction - Enum in network.aika
distanceFunction - Variable in class network.aika.neuron.Synapse.Builder
distanceFunction - Variable in class network.aika.neuron.Synapse
distanceFunction - Variable in class network.aika.training.SynapseEvaluation.Result
doc - Variable in class network.aika.lattice.NodeActivation
doc - Variable in class network.aika.training.SupervisedTraining
docIdCounter - Variable in class network.aika.Model
docs - Variable in class network.aika.Model
Document - Class in network.aika: The Document class represents a single document which may be either used for processing a text or as training input.
Document(int, String, Model, int) - Constructor for class network.aika.Document
Document.ActKey - Class in network.aika
Document.Queue - Class in network.aika
Document.UpperBoundQueue - Class in network.aika
Document.ValueQueue - Class in network.aika
dumpDebugCandidateStatistics() - Method in class network.aika.Document
dumpDebugState() - Method in class network.aika.neuron.activation.SearchNode
dumpOscillatingActivations() - Method in class network.aika.Document

E

ENABLE_CACHING - Static variable in class network.aika.neuron.activation.SearchNode
end - Variable in class network.aika.neuron.activation.Range
END - Static variable in class network.aika.neuron.activation.Range.Output
end - Variable in class network.aika.neuron.activation.Range.Output
END_COMP - Static variable in class network.aika.neuron.activation.Range
END_COMP - Static variable in class network.aika.neuron.INeuron
END_EQUALS - Static variable in class network.aika.neuron.activation.Range.Relation
END_TO_BEGIN_EQUALS - Static variable in class network.aika.neuron.activation.Range.Relation
endToBegin - Variable in class network.aika.neuron.activation.Range.Relation
endToEnd - Variable in class network.aika.neuron.activation.Range.Relation
equals(Activation.State) - Method in class network.aika.neuron.activation.Activation.State
equals(Range) - Method in class network.aika.neuron.activation.Range
EQUALS - Static variable in class network.aika.neuron.activation.Range.Relation
equals(Object) - Method in class network.aika.Provider
equalsWithWeights(Activation.State) - Method in class network.aika.neuron.activation.Activation.State
errorSignal - Variable in class network.aika.neuron.activation.Activation
errorSignalActivations - Variable in class network.aika.training.SupervisedTraining
evaluate(Synapse, Activation, Activation) - Method in interface network.aika.training.SynapseEvaluation: Determines whether a synapse should be created between two neurons during training.
exists() - Method in class network.aika.neuron.Synapse
extend(int, Document, AndNode.Refinement, PatternDiscovery.Config) - Method in class network.aika.lattice.AndNode
extend(int, Document, AndNode.Refinement, PatternDiscovery.Config) - Method in class network.aika.lattice.InputNode
extend(int, Document, AndNode.Refinement, PatternDiscovery.Config) - Method in class network.aika.lattice.Node
extend(int, Document, AndNode.Refinement, PatternDiscovery.Config) - Method in class network.aika.lattice.OrNode

F

f(double) - Method in enum network.aika.ActivationFunction
f(Activation, Activation) - Method in enum network.aika.DistanceFunction
finalDecision - Variable in class network.aika.neuron.activation.Activation
finallyActivatedNeurons - Variable in class network.aika.Document
finalRounds - Variable in class network.aika.neuron.activation.Activation
fired - Variable in class network.aika.neuron.activation.Activation.Builder
fired - Variable in class network.aika.neuron.activation.Activation.State

G

generateCandidates() - Method in class network.aika.Document
generateOutputText() - Method in class network.aika.Document
get(int) - Method in class network.aika.lattice.AndNode.RelationsMap
get(int) - Method in class network.aika.neuron.activation.Activation.Rounds
get() - Method in class network.aika.Provider
get(int) - Method in class network.aika.Provider
get(Document) - Method in class network.aika.Provider
getActivation() - Method in class network.aika.neuron.activation.Activation.StateChange
getActivation(Document, Range, boolean) - Method in class network.aika.neuron.INeuron
getActivation(Document, Range, boolean) - Method in class network.aika.neuron.Neuron
getActivations(boolean) - Method in class network.aika.Document
getActivations(Document) - Method in class network.aika.lattice.Node
getActivations(Document, boolean) - Method in class network.aika.neuron.INeuron
getActivations(Document, boolean) - Method in class network.aika.neuron.Neuron: getFinalActivations is a convenience method to retrieve all activations of the given neuron that are part of the final interpretation.
getActivations(INeuron, Activation) - Method in class network.aika.neuron.relation.InstanceRelation
getActivations(INeuron, Activation) - Method in class network.aika.neuron.relation.RangeRelation
getActivations(INeuron, Activation) - Method in class network.aika.neuron.relation.Relation
getActivationsByRangeEquals(INeuron.ThreadState, Range, Range.Relation) - Static method in class network.aika.neuron.relation.RangeRelation
getActivationsByRangeEquals(Document, Range, Range.Relation) - Static method in class network.aika.neuron.relation.RangeRelation
getActivationValue(Synapse, Activation) - Method in interface network.aika.PassiveInputFunction
getAllActivationsStream() - Method in class network.aika.Document
getAllNodeIds() - Method in interface network.aika.SuspensionHook
getBegin(boolean) - Method in class network.aika.neuron.activation.Range
getById(int) - Static method in enum network.aika.neuron.activation.Range.Mapping
getById(int) - Static method in enum network.aika.neuron.activation.Range.Operator
getConflicts() - Method in class network.aika.neuron.activation.Activation
getContent() - Method in class network.aika.Document
getDecision() - Method in class network.aika.neuron.activation.SearchNode
getEnd(boolean) - Method in class network.aika.neuron.activation.Range
getFinalInputActivationLinks() - Method in class network.aika.neuron.activation.Activation
getFinalOutputActivationLinks() - Method in class network.aika.neuron.activation.Activation
getFinalState() - Method in class network.aika.neuron.activation.Activation
getId() - Method in enum network.aika.neuron.activation.Range.Mapping
getId() - Method in enum network.aika.neuron.activation.Range.Operator
getIfNotSuspended() - Method in class network.aika.Provider
getINeuron() - Method in class network.aika.neuron.activation.Activation
getInputActivation(int) - Method in class network.aika.lattice.AndNode.AndActivation
getInputActivation(int) - Method in class network.aika.lattice.InputNode.InputActivation
getInputActivation(int) - Method in class network.aika.lattice.NodeActivation
getInputActivation(int) - Method in class network.aika.lattice.OrNode.OrActivation
getLabel() - Method in class network.aika.neuron.activation.Activation
getLabel() - Method in class network.aika.neuron.Neuron
getLast() - Method in class network.aika.neuron.activation.Activation.Rounds
getLastRound() - Method in class network.aika.neuron.activation.Activation.Rounds
getNeuron() - Method in class network.aika.neuron.activation.Activation
getNeuronLabel() - Method in class network.aika.lattice.Node
getNeuronLabel() - Method in class network.aika.lattice.OrNode
getNeuronStatisticFactory() - Method in class network.aika.Model
getNewBias() - Method in class network.aika.neuron.Synapse
getNewBiasSum() - Method in class network.aika.neuron.INeuron
getNewId() - Method in interface network.aika.SuspensionHook
getNewWeight() - Method in class network.aika.neuron.Synapse
getNodeStatisticFactory() - Method in class network.aika.Model
getOldestDocIdInProcessing() - Method in class network.aika.Model
getParent() - Method in class network.aika.neuron.activation.SearchNode
getRelations(Activation, Activation) - Static method in class network.aika.lattice.InputNode
getSequence() - Method in class network.aika.neuron.activation.Activation
getSuspensionHook() - Method in class network.aika.Model
getSynapse(Neuron) - Method in class network.aika.neuron.Synapse.Builder
getSynapseById(int) - Method in class network.aika.neuron.Neuron
getSynapseStatisticFactory() - Method in class network.aika.Model
getTarget() - Method in class network.aika.neuron.activation.Activation
getText(Range) - Method in class network.aika.Document
getText() - Method in class network.aika.neuron.activation.Activation
getThreadState(int, boolean) - Method in class network.aika.lattice.Node
getThreadState(int, boolean) - Method in class network.aika.neuron.INeuron

H

hashCode() - Method in class network.aika.Provider

I

id - Variable in class network.aika.Document
id - Variable in class network.aika.lattice.NodeActivation
id - Variable in class network.aika.neuron.activation.Candidate
id - Variable in class network.aika.neuron.activation.SearchNode
id - Variable in class network.aika.neuron.Synapse
id - Variable in class network.aika.Provider
identity - Variable in class network.aika.neuron.Synapse.Builder
identity - Variable in class network.aika.neuron.Synapse.Key
inactive - Variable in class network.aika.neuron.Synapse
includesEqual() - Method in enum network.aika.neuron.activation.Range.Operator
INCREMENTAL_MODE - Static variable in class network.aika.Document: Experimental code: not working yet!
INeuron - Class in network.aika.neuron: The INeuron class represents a internal neuron implementation in Aikas neural network and is connected to other neurons through input synapses and output synapses.
INeuron(Model) - Constructor for class network.aika.neuron.INeuron
INeuron(Model, String) - Constructor for class network.aika.neuron.INeuron
INeuron(Model, String, String) - Constructor for class network.aika.neuron.INeuron
INeuron.ActKey - Class in network.aika.neuron
INeuron.LogicType - Enum in network.aika.neuron
INeuron.ThreadState - Class in network.aika.neuron: The ThreadState is a thread local data structure containing the activations of a single document for a specific logic node.
INeuron.Type - Enum in network.aika.neuron
init(Neuron, double, INeuron.Type, INeuron.LogicType, Synapse.Builder...) - Static method in class network.aika.neuron.Neuron: Creates a neuron with the given bias.
init(Document, Neuron, double, INeuron.Type, INeuron.LogicType, Synapse.Builder...) - Static method in class network.aika.neuron.Neuron: Creates a neuron with the given bias.
init(Neuron, double, ActivationFunction, INeuron.Type, INeuron.LogicType, Synapse.Builder...) - Static method in class network.aika.neuron.Neuron: Creates a neuron with the given bias.
init(Document, Neuron, double, ActivationFunction, INeuron.Type, INeuron.LogicType, Synapse.Builder...) - Static method in class network.aika.neuron.Neuron: Creates a neuron with the given bias.
init(Neuron, double, INeuron.Type, INeuron.LogicType, List<Synapse.Builder>) - Static method in class network.aika.neuron.Neuron: Creates a neuron with the given bias.
init(Neuron, double, ActivationFunction, INeuron.Type, INeuron.LogicType, List<Synapse.Builder>) - Static method in class network.aika.neuron.Neuron: Initializes a neuron with the given bias.
init(Document, Neuron, double, ActivationFunction, INeuron.Type, INeuron.LogicType, List<Synapse.Builder>) - Static method in class network.aika.neuron.Neuron: Initializes a neuron with the given bias.
init(double, ActivationFunction, INeuron.Type, INeuron.LogicType, List<Synapse.Builder>) - Method in class network.aika.neuron.Neuron: Initializes a neuron with the given bias.
init(Document, double, ActivationFunction, INeuron.Type, INeuron.LogicType, List<Synapse.Builder>) - Method in class network.aika.neuron.Neuron
inMemoryInputSynapses - Variable in class network.aika.neuron.Neuron
inMemoryOutputSynapses - Variable in class network.aika.neuron.Neuron
input - Variable in class network.aika.lattice.AndNode.Link
input - Variable in class network.aika.lattice.AndNode.Refinement
input - Variable in class network.aika.lattice.InputNode.InputActivation
input - Variable in class network.aika.lattice.InputNode.Link
input - Variable in class network.aika.lattice.OrNode.Link
input - Variable in class network.aika.neuron.activation.Activation.Link
input - Variable in class network.aika.neuron.Synapse
INPUT_COMP - Static variable in class network.aika.neuron.activation.Activation.Link
INPUT_SYNAPSE_COMP - Static variable in class network.aika.neuron.Synapse
InputActivation(int, Activation, InputNode) - Constructor for class network.aika.lattice.InputNode.InputActivation
inputDecision - Variable in class network.aika.neuron.activation.Activation
inputNeuron - Variable in class network.aika.lattice.InputNode
inputNeuronActivations - Variable in class network.aika.Document
InputNode - Class in network.aika.lattice: The InputNode class is the input layer for the boolean logic.
InputNode() - Constructor for class network.aika.lattice.InputNode
InputNode(Model) - Constructor for class network.aika.lattice.InputNode
InputNode.InputActivation - Class in network.aika.lattice
InputNode.Link - Class in network.aika.lattice
inputs - Variable in class network.aika.lattice.AndNode.AndActivation
inputs - Variable in class network.aika.lattice.OrNode.OrActivation
inputSynapses - Variable in class network.aika.neuron.INeuron
inputSynapsesById - Variable in class network.aika.neuron.Neuron
inputValue - Variable in class network.aika.neuron.activation.Activation
InstanceRelation - Class in network.aika.neuron.relation
InstanceRelation(InstanceRelation.Type) - Constructor for class network.aika.neuron.relation.InstanceRelation
InstanceRelation.Type - Enum in network.aika.neuron.relation
invalidateCachedDecision(Activation) - Static method in class network.aika.neuron.activation.SearchNode
invert(boolean) - Method in class network.aika.neuron.activation.Range
invert() - Method in enum network.aika.neuron.activation.Range.Operator
invert() - Method in class network.aika.neuron.activation.Range.Output
invert() - Method in class network.aika.neuron.activation.Range.Relation
invert() - Method in class network.aika.neuron.relation.InstanceRelation
invert() - Method in class network.aika.neuron.relation.RangeRelation
invert() - Method in class network.aika.neuron.relation.Relation
isActive() - Method in class network.aika.neuron.activation.Activation.Rounds
isConflicting() - Method in class network.aika.neuron.activation.Candidate
isConjunction - Variable in class network.aika.neuron.Synapse: The synapse is stored either in the input neuron or the output neuron depending on whether it is a conjunctive or disjunctive synapse.
isConjunction(boolean, boolean) - Method in class network.aika.neuron.Synapse
isDiscovered - Variable in class network.aika.lattice.Node
isEmpty() - Method in class network.aika.neuron.activation.Range
isExact() - Method in class network.aika.lattice.AndNode.RelationsMap
isExact() - Method in class network.aika.neuron.relation.InstanceRelation
isExact() - Method in class network.aika.neuron.relation.RangeRelation
isExact() - Method in class network.aika.neuron.relation.Relation
isFinalActivation() - Method in class network.aika.neuron.activation.Activation
isGreaterThanOrGreaterThanEqual() - Method in enum network.aika.neuron.activation.Range.Operator
isLessThanOrLessThanEqual() - Method in enum network.aika.neuron.activation.Range.Operator
isMeta - Variable in class network.aika.neuron.INeuron
isNegative() - Method in class network.aika.neuron.Synapse
isPassiveInputNeuron() - Method in class network.aika.neuron.INeuron
isQueued - Variable in class network.aika.lattice.Node.ThreadState
isQueued - Variable in class network.aika.neuron.activation.Activation
isQueued(int) - Method in class network.aika.neuron.activation.Activation.Rounds
isRecurrent - Variable in class network.aika.neuron.Synapse.Key
isRequired() - Method in class network.aika.lattice.Node
isSuspended() - Method in class network.aika.Provider

K

key - Variable in class network.aika.neuron.Synapse
Key(boolean, int, Range.Output, boolean) - Constructor for class network.aika.neuron.Synapse.Key

L

label - Variable in class network.aika.neuron.INeuron
lastCleanup - Variable in class network.aika.Model
lastUsed - Variable in class network.aika.lattice.Node.ThreadState
lastUsed - Variable in class network.aika.neuron.INeuron.ThreadState
lastUsedDocumentId - Variable in class network.aika.AbstractNode
lateLinking() - Method in class network.aika.neuron.activation.Linker
learnRate - Variable in class network.aika.training.SupervisedTraining.Config
length() - Method in class network.aika.Document
length() - Method in class network.aika.lattice.AndNode.RelationsMap
length() - Method in class network.aika.neuron.activation.Range
level - Variable in class network.aika.lattice.Node
link(AndNode.Refinement, AndNode.RefValue, InputNode.InputActivation, NodeActivation<?>) - Method in class network.aika.lattice.AndNode.AndActivation
Link(AndNode.Refinement, AndNode.RefValue, InputNode.InputActivation, NodeActivation<?>, AndNode.AndActivation) - Constructor for class network.aika.lattice.AndNode.Link
Link(Activation, InputNode.InputActivation) - Constructor for class network.aika.lattice.InputNode.Link
Link(OrNode.OrEntry, NodeActivation<?>, OrNode.OrActivation) - Constructor for class network.aika.lattice.OrNode.Link
link(OrNode.OrEntry, NodeActivation<?>) - Method in class network.aika.lattice.OrNode.OrActivation
Link(Synapse, Activation, Activation) - Constructor for class network.aika.neuron.activation.Activation.Link
link(Activation, OrNode.Link) - Method in class network.aika.neuron.activation.Linker: Adds the incoming links between neuron activations.
link() - Method in class network.aika.neuron.Synapse
linker - Variable in class network.aika.Document
Linker - Class in network.aika.neuron.activation: The Linker class is responsible for for the linkage of neuron activations.
Linker(Document) - Constructor for class network.aika.neuron.activation.Linker
Linker.Direction - Enum in network.aika.neuron.activation
linksToString() - Method in class network.aika.neuron.activation.Activation
lock - Variable in class network.aika.lattice.Node
lock - Variable in class network.aika.neuron.INeuron
lock - Variable in class network.aika.neuron.Neuron
logicToString() - Method in class network.aika.lattice.AndNode
logicToString() - Method in class network.aika.lattice.InputNode
logicToString() - Method in class network.aika.lattice.Node
logicToString() - Method in class network.aika.lattice.OrNode
logicType - Variable in class network.aika.neuron.INeuron
lookup(Range.Output) - Static method in class network.aika.neuron.activation.Range.Output
lookup(Range.Relation) - Static method in class network.aika.neuron.activation.Range.Relation
lookupKey(Synapse.Key) - Static method in class network.aika.neuron.Synapse
lookupNeuron(int) - Method in class network.aika.Model
lookupNodeProvider(int) - Method in class network.aika.Model
lowerBound - Variable in class network.aika.neuron.activation.Activation

M

map(Range) - Method in enum network.aika.neuron.activation.Range.Mapping
map(Range) - Method in class network.aika.neuron.activation.Range.Output
markDirty(long) - Method in class network.aika.neuron.activation.Activation
markedAncestor - Variable in class network.aika.neuron.activation.Activation
markedCreated - Variable in class network.aika.lattice.Node
markedDirty - Variable in class network.aika.neuron.activation.Activation
markedHasCandidate - Variable in class network.aika.neuron.activation.Activation
markedPredecessor - Variable in class network.aika.neuron.activation.Activation
markPredecessor(long, int) - Method in class network.aika.neuron.activation.Activation
MAX - Static variable in class network.aika.lattice.AndNode.RelationsMap
MAX_ACTIVATION - Static variable in class network.aika.neuron.activation.Activation
MAX_AND_NODE_SIZE - Static variable in class network.aika.Converter
MAX_NEURON - Static variable in class network.aika.neuron.Neuron
MAX_NODE - Static variable in class network.aika.lattice.Node
MAX_PREDECESSOR_DEPTH - Static variable in class network.aika.neuron.activation.Activation
MAX_ROUND - Static variable in class network.aika.Document
MAX_SEARCH_STEPS - Static variable in class network.aika.neuron.activation.SearchNode
MAX_SELF_REFERENCING_DEPTH - Static variable in class network.aika.neuron.activation.Activation
maxLength - Variable in class network.aika.neuron.INeuron.ThreadState
metaBias - Variable in class network.aika.neuron.INeuron
MIN - Static variable in class network.aika.lattice.AndNode.RelationsMap
MIN_ACTIVATION - Static variable in class network.aika.neuron.activation.Activation
MIN_NEURON - Static variable in class network.aika.neuron.Neuron
MIN_NODE - Static variable in class network.aika.lattice.Node
minLength - Variable in class network.aika.neuron.INeuron.ThreadState
model - Variable in class network.aika.Document
Model - Class in network.aika: The model consists of two layers.
Model() - Constructor for class network.aika.Model: Creates a model with a single thread.
Model(SuspensionHook, int) - Constructor for class network.aika.Model
model - Variable in class network.aika.Provider
Model.WritableFactory - Interface in network.aika
modified - Variable in class network.aika.AbstractNode
modifiedActs - Variable in class network.aika.neuron.activation.SearchNode
modifiedWeights - Variable in class network.aika.Document

N

NEGATIVE - Static variable in class network.aika.Converter
negDirSum - Variable in class network.aika.neuron.INeuron
negRecSum - Variable in class network.aika.neuron.INeuron
net - Variable in class network.aika.neuron.activation.Activation.State
network.aika - package network.aika
network.aika.lattice - package network.aika.lattice
network.aika.neuron - package network.aika.neuron
network.aika.neuron.activation - package network.aika.neuron.activation
network.aika.neuron.relation - package network.aika.neuron.relation
network.aika.training - package network.aika.training
neuron - Variable in class network.aika.lattice.OrNode
Neuron - Class in network.aika.neuron: The Neuron class is a proxy implementation for the real neuron implementation in the class INeuron.
Neuron(Model, int) - Constructor for class network.aika.neuron.Neuron
Neuron(Model, INeuron) - Constructor for class network.aika.neuron.Neuron
neuron - Variable in class network.aika.neuron.Synapse.Builder
neuronInputs - Variable in class network.aika.neuron.activation.Activation
neuronOutputs - Variable in class network.aika.neuron.activation.Activation
neuronStatisticFactory - Variable in class network.aika.Model
newRounds - Variable in class network.aika.neuron.activation.Activation.StateChange
newState - Variable in class network.aika.neuron.activation.Activation.StateChange
Node<T extends Node,A extends NodeActivation<T>> - Class in network.aika.lattice: The Node class is the abstract class for all the boolean logic nodes underneath the neural network layer.
Node() - Constructor for class network.aika.lattice.Node
Node(Model, int) - Constructor for class network.aika.lattice.Node
node - Variable in class network.aika.lattice.NodeActivation
node - Variable in class network.aika.neuron.INeuron
Node.ThreadState<T extends Node,A extends NodeActivation> - Class in network.aika.lattice: The ThreadState is a thread local data structure containing the activations of a single document for a specific logic node.
NodeActivation<T extends Node> - Class in network.aika.lattice
NodeActivation(int, Document, T) - Constructor for class network.aika.lattice.NodeActivation
nodeStatisticFactory - Variable in class network.aika.Model
NONE - Static variable in class network.aika.neuron.activation.Range.Output
NONE - Static variable in class network.aika.neuron.activation.Range.Relation
nonExactAndChildren - Variable in class network.aika.lattice.InputNode
notifyWeightModified(Synapse) - Method in class network.aika.Document
nullSafeAdd(Integer, boolean, Integer, boolean) - Static method in class network.aika.Utils
nullSafeMax(Integer, Integer) - Static method in class network.aika.Utils
nullSafeMax(Double, Double) - Static method in class network.aika.Utils
nullSafeMin(Integer, Integer) - Static method in class network.aika.Utils
nullSafeSub(Integer, boolean, Integer, boolean) - Static method in class network.aika.Utils
numberOfInputSynapses - Variable in class network.aika.neuron.INeuron
numberOfNeuronRefs - Variable in class network.aika.lattice.Node
numberOfThreads - Variable in class network.aika.Model
numDisjunctiveSynapses - Variable in class network.aika.neuron.INeuron

O

oe - Variable in class network.aika.lattice.OrNode.Link
offsets - Variable in class network.aika.lattice.AndNode.RefValue
oldRounds - Variable in class network.aika.neuron.activation.Activation.StateChange
OPTIMIZE_SEARCH - Static variable in class network.aika.neuron.activation.SearchNode
OrActivation(int, Document, OrNode) - Constructor for class network.aika.lattice.OrNode.OrActivation
orChildren - Variable in class network.aika.lattice.Node
OrEntry(int[], Provider<? extends Node>, Provider<OrNode>) - Constructor for class network.aika.lattice.OrNode.OrEntry
OrNode - Class in network.aika.lattice: While several neurons might share a the same input-node or and-node, there is always a always a one-to-one relation between or-nodes and neurons.
OrNode() - Constructor for class network.aika.lattice.OrNode
OrNode(Model) - Constructor for class network.aika.lattice.OrNode
OrNode.Link - Class in network.aika.lattice
OrNode.OrActivation - Class in network.aika.lattice
OrNode.OrEntry - Class in network.aika.lattice
output - Variable in class network.aika.lattice.AndNode.Link
output - Variable in class network.aika.lattice.InputNode.Link
output - Variable in class network.aika.lattice.OrNode.Link
output - Variable in class network.aika.neuron.activation.Activation.Link
OUTPUT - Static variable in class network.aika.neuron.Synapse.Builder
output - Variable in class network.aika.neuron.Synapse
OUTPUT_COMP - Static variable in class network.aika.neuron.activation.Activation.Link
OUTPUT_SYNAPSE_COMP - Static variable in class network.aika.neuron.Synapse
outputNode - Variable in class network.aika.neuron.INeuron
outputRelations - Variable in class network.aika.neuron.INeuron
outputsToAndNode - Variable in class network.aika.lattice.NodeActivation
outputsToOrNode - Variable in class network.aika.lattice.NodeActivation
outputSynapses - Variable in class network.aika.neuron.INeuron
outputText - Variable in class network.aika.neuron.INeuron
outputToInputNode - Variable in class network.aika.lattice.NodeActivation
overlaps(Range, Range) - Static method in class network.aika.neuron.activation.Range: Deprecated.
OVERLAPS - Static variable in class network.aika.neuron.activation.Range.Relation

P

p - Variable in class network.aika.neuron.activation.Activation.State
parent - Variable in class network.aika.lattice.AndNode.RefValue
parent - Variable in class network.aika.lattice.OrNode.OrEntry
parents - Variable in class network.aika.lattice.AndNode
passiveActivationFunctions - Variable in class network.aika.Model
passiveInputFunction - Variable in class network.aika.neuron.INeuron
PassiveInputFunction - Interface in network.aika
passiveInputSynapses - Variable in class network.aika.neuron.INeuron
pathToString() - Method in class network.aika.neuron.activation.SearchNode
patternCheck - Variable in class network.aika.training.PatternDiscovery.Config
PatternDiscovery - Class in network.aika.training
PatternDiscovery() - Constructor for class network.aika.training.PatternDiscovery
PatternDiscovery.CandidateCheck - Interface in network.aika.training
PatternDiscovery.Config - Class in network.aika.training
PatternDiscovery.Counter - Interface in network.aika.training
PatternDiscovery.PatternCheck - Interface in network.aika.training
performBackpropagation - Variable in class network.aika.training.SupervisedTraining.Config
posDirSum - Variable in class network.aika.neuron.INeuron
POSITIVE - Static variable in class network.aika.Converter
posNet - Variable in class network.aika.neuron.activation.Activation.State
posPassiveSum - Variable in class network.aika.neuron.INeuron
posRecSum - Variable in class network.aika.neuron.INeuron
postCreate(Document) - Method in class network.aika.lattice.Node
posValue - Variable in class network.aika.neuron.activation.Activation.State
process() - Method in class network.aika.Document: The method process needs to be called after all the input activations have been added to the network.
process(Long) - Method in class network.aika.Document
process() - Method in class network.aika.Document.UpperBoundQueue
process(SearchNode) - Method in class network.aika.Document.ValueQueue
process(SearchNode, int, long) - Method in class network.aika.neuron.activation.Activation
process() - Method in class network.aika.neuron.activation.Linker
processBounds() - Method in class network.aika.neuron.activation.Activation
processCandidate(Node<?, ? extends NodeActivation<?>>, NodeActivation, boolean) - Static method in class network.aika.lattice.OrNode
processChanges() - Method in class network.aika.Document.Queue
processChanges(Document) - Method in class network.aika.lattice.Node: Process all added or removed activation for this logic node.
propagate(A) - Method in class network.aika.AbstractNode: Propagate an activation to the next node or the next neuron that is depending on the current node.
propagate() - Method in class network.aika.Document
propagate(AndNode.AndActivation) - Method in class network.aika.lattice.AndNode
propagate(InputNode.InputActivation) - Method in class network.aika.lattice.InputNode
propagate(Activation) - Method in class network.aika.lattice.OrNode
propagate(Activation) - Method in class network.aika.neuron.INeuron
propagateActivationValue(int, Activation) - Method in class network.aika.Document.ValueQueue
provider - Variable in class network.aika.AbstractNode
Provider<T extends AbstractNode> - Class in network.aika
Provider(Model, int) - Constructor for class network.aika.Provider
Provider(Model, T) - Constructor for class network.aika.Provider
Provider.SuspensionMode - Enum in network.aika
providers - Variable in class network.aika.Model

Q

queue - Variable in class network.aika.Document
Queue() - Constructor for class network.aika.Document.Queue
queue - Variable in class network.aika.Document.Queue
queue - Variable in class network.aika.Document.UpperBoundQueue
queue - Variable in class network.aika.Document.ValueQueue
queue - Variable in class network.aika.training.SupervisedTraining.BackPropagationQueue
queue - Variable in class network.aika.training.SupervisedTraining
queueId - Variable in class network.aika.lattice.Node.ThreadState
queueId - Variable in class network.aika.neuron.activation.Activation

R

range - Variable in class network.aika.neuron.activation.Activation.Builder
range - Variable in class network.aika.neuron.activation.Activation
Range - Class in network.aika.neuron.activation: The class Range specifies a text range (begin char pos, end char pos) within a given document.
Range(Integer, Integer) - Constructor for class network.aika.neuron.activation.Range
Range.Mapping - Enum in network.aika.neuron.activation
Range.Operator - Enum in network.aika.neuron.activation
Range.Output - Class in network.aika.neuron.activation
Range.Relation - Class in network.aika.neuron.activation
rangeInput - Variable in class network.aika.neuron.Synapse.Builder
rangeInput - Variable in class network.aika.neuron.Synapse.Key
rangeOutput - Variable in class network.aika.neuron.Synapse.Builder
rangeOutput - Variable in class network.aika.neuron.Synapse.Key
RangeRelation - Class in network.aika.neuron.relation
RangeRelation(Range.Relation) - Constructor for class network.aika.neuron.relation.RangeRelation
reactivate() - Method in class network.aika.AbstractNode
reactivate() - Method in class network.aika.neuron.INeuron
read(DataInput, P) - Static method in class network.aika.AbstractNode
read(DataInput, Model) - Static method in class network.aika.lattice.AndNode.Refinement
read(DataInput, Model) - Static method in class network.aika.lattice.AndNode.RefValue
read(DataInput, Model) - Static method in class network.aika.lattice.AndNode.RelationsMap
read(DataInput, Model) - Static method in class network.aika.lattice.OrNode.OrEntry
read(DataInput, Model) - Static method in class network.aika.neuron.activation.Range.Output
read(DataInput, Model) - Static method in class network.aika.neuron.activation.Range.Relation
read(DataInput, Model) - Static method in class network.aika.neuron.relation.InstanceRelation
read(DataInput, Model) - Static method in class network.aika.neuron.relation.RangeRelation
read(DataInput, Model) - Static method in class network.aika.neuron.relation.Relation
read(DataInput, Model) - Static method in class network.aika.neuron.Synapse.Key
read(DataInput, Model) - Static method in class network.aika.neuron.Synapse
readFields(DataInput, Model) - Method in class network.aika.lattice.AndNode
readFields(DataInput, Model) - Method in class network.aika.lattice.AndNode.Refinement
readFields(DataInput, Model) - Method in class network.aika.lattice.AndNode.RefValue
readFields(DataInput, Model) - Method in class network.aika.lattice.AndNode.RelationsMap
readFields(DataInput, Model) - Method in class network.aika.lattice.InputNode
readFields(DataInput, Model) - Method in class network.aika.lattice.Node
readFields(DataInput, Model) - Method in class network.aika.lattice.OrNode.OrEntry
readFields(DataInput, Model) - Method in class network.aika.lattice.OrNode
readFields(DataInput, Model) - Method in class network.aika.neuron.activation.Range.Output
readFields(DataInput, Model) - Method in class network.aika.neuron.activation.Range.Relation
readFields(DataInput, Model) - Method in class network.aika.neuron.INeuron
readFields(DataInput, Model) - Method in class network.aika.neuron.relation.InstanceRelation
readFields(DataInput, Model) - Method in class network.aika.neuron.relation.RangeRelation
readFields(DataInput, Model) - Method in class network.aika.neuron.Synapse.Key
readFields(DataInput, Model) - Method in class network.aika.neuron.Synapse
readFields(DataInput, Model) - Method in interface network.aika.Writable: Deserialize the fields of this object from in.
readNeuron(DataInput, Neuron) - Static method in class network.aika.neuron.INeuron
readNode(DataInput, Provider) - Static method in class network.aika.lattice.Node
ReadWriteLock - Class in network.aika
ReadWriteLock() - Constructor for class network.aika.ReadWriteLock
RECURRENT - Static variable in class network.aika.Converter
recurrent - Variable in class network.aika.neuron.Synapse.Builder
ref - Variable in class network.aika.lattice.AndNode.Link
refAct - Variable in class network.aika.lattice.AndNode.Link
Refinement(AndNode.RelationsMap, Provider<InputNode>) - Constructor for class network.aika.lattice.AndNode.Refinement
refOffset - Variable in class network.aika.lattice.AndNode.RefValue
RefValue(Integer[], int, Provider<? extends Node>) - Constructor for class network.aika.lattice.AndNode.RefValue
register(A) - Method in class network.aika.lattice.Node
register(Provider) - Method in class network.aika.Model
register(Activation) - Method in class network.aika.neuron.INeuron
registerPassiveInputNeuron(Neuron, PassiveInputFunction) - Static method in class network.aika.neuron.Neuron
registerPassiveInputSynapse(Synapse) - Method in class network.aika.neuron.INeuron
Relation() - Constructor for class network.aika.neuron.activation.Range.Relation
relation - Variable in class network.aika.neuron.relation.RangeRelation
Relation - Class in network.aika.neuron.relation
Relation() - Constructor for class network.aika.neuron.relation.Relation
relations - Variable in class network.aika.lattice.AndNode.Refinement
relations - Variable in class network.aika.lattice.AndNode.RelationsMap
relations - Variable in class network.aika.neuron.Synapse.Builder
relations - Variable in class network.aika.neuron.Synapse
relations - Variable in class network.aika.training.SynapseEvaluation.Result
RelationsMap() - Constructor for class network.aika.lattice.AndNode.RelationsMap
RelationsMap(Relation[]) - Constructor for class network.aika.lattice.AndNode.RelationsMap
releaseReadLock() - Method in class network.aika.ReadWriteLock
releaseWriteLock() - Method in class network.aika.ReadWriteLock
relink() - Method in class network.aika.neuron.Synapse
remove() - Method in class network.aika.lattice.AndNode
remove() - Method in class network.aika.lattice.Node
remove() - Method in class network.aika.neuron.INeuron
removeInMemoryInputSynapse(Synapse) - Method in class network.aika.neuron.Neuron
removeInMemoryOutputSynapse(Synapse) - Method in class network.aika.neuron.Neuron
removeParents(int) - Method in class network.aika.lattice.OrNode
removeProvider(Provider) - Method in class network.aika.Model
repeat - Variable in class network.aika.neuron.activation.Candidate
reprocessInputs(Document) - Method in class network.aika.lattice.AndNode
reprocessInputs(Document) - Method in class network.aika.lattice.InputNode
reprocessInputs(Document) - Method in class network.aika.lattice.Node
reprocessInputs(Document) - Method in class network.aika.lattice.OrNode
repropagateV - Variable in class network.aika.lattice.NodeActivation
requiredSum - Variable in class network.aika.neuron.INeuron
reset() - Method in class network.aika.neuron.activation.Activation.Rounds
restoreState(Activation.Mode) - Method in class network.aika.neuron.activation.Activation.StateChange
Result(Synapse.Key, Map<Integer, Relation>, DistanceFunction, double, SynapseEvaluation.DeleteMode) - Constructor for class network.aika.training.SynapseEvaluation.Result
retrieve(int) - Method in interface network.aika.SuspensionHook
reverseOffsets - Variable in class network.aika.lattice.AndNode.RefValue
revSynapseIds - Variable in class network.aika.lattice.OrNode.OrEntry
round(double) - Static method in class network.aika.Utils
rounds - Variable in class network.aika.neuron.activation.Activation
Rounds() - Constructor for class network.aika.neuron.activation.Activation.Rounds
rounds - Variable in class network.aika.neuron.activation.Activation.Rounds
rv - Variable in class network.aika.lattice.AndNode.Link

S

save() - Method in class network.aika.Provider
saveNewState() - Method in class network.aika.neuron.activation.Activation
saveOldState(Map<Activation, Activation.StateChange>, long) - Method in class network.aika.neuron.activation.Activation
search(Document, SearchNode, long, Long) - Static method in class network.aika.neuron.activation.SearchNode: Searches for the best interpretation for the given document.
SearchNode - Class in network.aika.neuron.activation: The SearchNode class represents a node in the binary search tree that is used to find the optimal interpretation for a given document.
SearchNode(Document, SearchNode, SearchNode, int) - Constructor for class network.aika.neuron.activation.SearchNode
SearchNode.DebugState - Enum in network.aika.neuron.activation
SearchNode.Decision - Enum in network.aika.neuron.activation
SearchNode.TimeoutException - Exception in network.aika.neuron.activation
searchNodeIdCounter - Variable in class network.aika.Document
searchNodeWeights - Variable in class network.aika.Document
searchStates - Variable in class network.aika.neuron.activation.Activation
searchStepCounter - Variable in class network.aika.Document
selectedNeuronInputs - Variable in class network.aika.neuron.activation.Activation
selectedSearchNode - Variable in class network.aika.Document
sequence - Variable in class network.aika.neuron.activation.Activation
set(int, Activation.State) - Method in class network.aika.neuron.activation.Activation.Rounds
setBias(double) - Method in class network.aika.neuron.INeuron
setBias(double) - Method in class network.aika.neuron.Synapse.Builder: The bias of this input that will later on be added to the neurons bias.
setCandidateCheck(PatternDiscovery.CandidateCheck) - Method in class network.aika.training.PatternDiscovery.Config
setCounter(PatternDiscovery.Counter) - Method in class network.aika.training.PatternDiscovery.Config: The counter callback function should implement a customized counting function.
setDecision(SearchNode.Decision, long) - Method in class network.aika.neuron.activation.Activation
setDistanceFunction(DistanceFunction) - Method in class network.aika.neuron.Synapse.Builder
setFired(int) - Method in class network.aika.neuron.activation.Activation.Builder
setIdentity(boolean) - Method in class network.aika.neuron.Synapse.Builder
setLearnRate(double) - Method in class network.aika.training.SupervisedTraining.Config
setModified() - Method in class network.aika.AbstractNode
setNeuron(Neuron) - Method in class network.aika.neuron.Synapse.Builder: Determines the input neuron.
setNeuronStatisticFactory(Model.WritableFactory) - Method in class network.aika.Model
setNodeStatisticFactory(Model.WritableFactory) - Method in class network.aika.Model
setPatternCheck(PatternDiscovery.PatternCheck) - Method in class network.aika.training.PatternDiscovery.Config
setPerformBackpropagation(boolean) - Method in class network.aika.training.SupervisedTraining.Config
setQueued(int, boolean) - Method in class network.aika.neuron.activation.Activation.Rounds
setRange(int, int) - Method in class network.aika.neuron.activation.Activation.Builder
setRange(Range) - Method in class network.aika.neuron.activation.Activation.Builder
setRangeInput(int) - Method in class network.aika.neuron.Synapse.Builder: By default the output range of th synapses input neuron is used.
setRangeOutput(boolean) - Method in class network.aika.neuron.Synapse.Builder: setRangeOutput is just a convenience function to call setBeginRangeOutput and setEndRangeOutput at the same time.
setRangeOutput(boolean, boolean) - Method in class network.aika.neuron.Synapse.Builder: setRangeOutput is just a convenience function to call setBeginRangeOutput and setEndRangeOutput at the same time.
setRangeOutput(Range.Output) - Method in class network.aika.neuron.Synapse.Builder: setRangeOutput is just a convenience function to call setBeginRangeOutput and setEndRangeOutput at the same time.
setRangeOutput(Range.Mapping, Range.Mapping) - Method in class network.aika.neuron.Synapse.Builder: Determines if this input is used to compute the range start of the output activation.
setRecurrent(boolean) - Method in class network.aika.neuron.Synapse.Builder: The property recurrent specifies if input is a recurrent feedback link.
setSuspensionHook(SuspensionHook) - Method in class network.aika.Model
setSynapseEvaluation(SynapseEvaluation) - Method in class network.aika.training.SupervisedTraining.Config: Determines whether a synapse should be created between two neurons during training.
setSynapseId(int) - Method in class network.aika.neuron.Synapse.Builder
setSynapseStatisticFactory(Model.WritableFactory) - Method in class network.aika.Model
setTargetValue(Double) - Method in class network.aika.neuron.activation.Activation.Builder
setTargetValue(Double) - Method in class network.aika.neuron.activation.Activation
setValue(double) - Method in class network.aika.neuron.activation.Activation.Builder
setWeight(double) - Method in class network.aika.neuron.Synapse.Builder: The synapse weight of this input.
sigmoid(double) - Static method in class network.aika.Utils
significance - Variable in class network.aika.training.SynapseEvaluation.Result
size() - Method in class network.aika.lattice.AndNode.RelationsMap
State(double, double, double, double, double, int, double) - Constructor for class network.aika.neuron.activation.Activation.State
StateChange() - Constructor for class network.aika.neuron.activation.Activation.StateChange
statistic - Variable in class network.aika.lattice.Node
statistic - Variable in class network.aika.neuron.INeuron
statistic - Variable in class network.aika.neuron.Synapse
store(int, byte[]) - Method in interface network.aika.SuspensionHook
supervisedTraining - Variable in class network.aika.Document
SupervisedTraining - Class in network.aika.training
SupervisedTraining(Document) - Constructor for class network.aika.training.SupervisedTraining
SupervisedTraining.BackPropagationQueue - Class in network.aika.training
SupervisedTraining.Config - Class in network.aika.training
suspend() - Method in class network.aika.AbstractNode
suspend() - Method in class network.aika.neuron.INeuron
suspend(Provider.SuspensionMode) - Method in class network.aika.Provider
suspendAll(Provider.SuspensionMode) - Method in class network.aika.Model: Suspend all neurons and logic nodes in memory.
suspendUnusedNodes(int, Provider.SuspensionMode) - Method in class network.aika.Model: Suspend all neurons and logic nodes whose last used document id is lower/older than .
suspensionHook - Variable in class network.aika.Model
SuspensionHook - Interface in network.aika: The suspension hook is used to suspend neurons and logic nodes to an external storage in order to reduce the memory footprint. !!!
synapse - Variable in class network.aika.neuron.activation.Activation.Link
Synapse - Class in network.aika.neuron: The Synapse class connects two neurons with each other.
Synapse() - Constructor for class network.aika.neuron.Synapse
Synapse(Neuron, Neuron, Integer, Synapse.Key, Map<Integer, Relation>, DistanceFunction) - Constructor for class network.aika.neuron.Synapse
Synapse.Builder - Class in network.aika.neuron: The Builder class is just a helper class which is used to initialize a neuron.
Synapse.Key - Class in network.aika.neuron
SYNAPSE_COMP - Static variable in class network.aika.Converter
synapseEvaluation - Variable in class network.aika.training.SupervisedTraining.Config
SynapseEvaluation - Interface in network.aika.training
SynapseEvaluation.DeleteMode - Enum in network.aika.training
SynapseEvaluation.Result - Class in network.aika.training
synapseId - Variable in class network.aika.neuron.Synapse.Builder
synapseIds - Variable in class network.aika.lattice.OrNode.OrEntry
synapseKey - Variable in class network.aika.training.SynapseEvaluation.Result
synapseStatisticFactory - Variable in class network.aika.Model

T

targetActivations - Variable in class network.aika.training.SupervisedTraining
targetValue - Variable in class network.aika.neuron.activation.Activation.Builder
targetValue - Variable in class network.aika.neuron.activation.Activation
test(Activation, Activation) - Method in class network.aika.neuron.relation.InstanceRelation
test(Activation, Activation) - Method in class network.aika.neuron.relation.RangeRelation
test(Activation, Activation) - Method in class network.aika.neuron.relation.Relation
threadId - Variable in class network.aika.Document
threads - Variable in class network.aika.lattice.Node
threads - Variable in class network.aika.neuron.INeuron
ThreadState() - Constructor for class network.aika.lattice.Node.ThreadState
ThreadState() - Constructor for class network.aika.neuron.INeuron.ThreadState
TimeoutException(String) - Constructor for exception network.aika.neuron.activation.SearchNode.TimeoutException
toBeDeleted - Variable in class network.aika.neuron.Synapse
TOLERANCE - Static variable in class network.aika.neuron.INeuron
toString() - Method in class network.aika.Document
toString() - Method in class network.aika.lattice.AndNode.AndActivation
toString() - Method in class network.aika.lattice.AndNode.Refinement
toString() - Method in class network.aika.lattice.AndNode.RelationsMap
toString() - Method in class network.aika.lattice.InputNode.InputActivation
toString() - Method in class network.aika.lattice.Node
toString() - Method in class network.aika.neuron.activation.Activation.Link
toString() - Method in class network.aika.neuron.activation.Activation.Rounds
toString() - Method in class network.aika.neuron.activation.Activation.State
toString() - Method in class network.aika.neuron.activation.Activation
toString(boolean, boolean, boolean) - Method in class network.aika.neuron.activation.Activation
toString() - Method in class network.aika.neuron.activation.Candidate
toString() - Method in enum network.aika.neuron.activation.Range.Mapping
toString() - Method in class network.aika.neuron.activation.Range.Output
toString() - Method in class network.aika.neuron.activation.Range.Relation
toString() - Method in class network.aika.neuron.activation.Range
toString() - Method in class network.aika.neuron.activation.SearchNode
toString() - Method in class network.aika.neuron.INeuron
toString() - Method in class network.aika.neuron.Neuron
toString() - Method in class network.aika.neuron.relation.RangeRelation
toString() - Method in class network.aika.neuron.Synapse
toString() - Method in class network.aika.Provider
toStringWithSynapses() - Method in class network.aika.neuron.INeuron
train(SupervisedTraining.Config) - Method in class network.aika.training.SupervisedTraining
train(INeuron, Activation, double, SynapseEvaluation) - Method in class network.aika.training.SupervisedTraining
type - Variable in class network.aika.neuron.INeuron
type - Variable in class network.aika.neuron.relation.InstanceRelation

U

ubQueue - Variable in class network.aika.Document
ubQueued - Variable in class network.aika.neuron.activation.Activation
unlink() - Method in class network.aika.neuron.Synapse
unregister(Provider) - Method in class network.aika.Model
update(int, Document, Neuron, Double, Collection<Synapse>) - Static method in class network.aika.neuron.INeuron
update(Document, double, double) - Method in class network.aika.neuron.Synapse
updateDelta(Document, double, double) - Method in class network.aika.neuron.Synapse
updateErrorSignal(Activation) - Method in class network.aika.training.SupervisedTraining
upperBound - Variable in class network.aika.neuron.activation.Activation
UpperBoundQueue() - Constructor for class network.aika.Document.UpperBoundQueue
Utils - Class in network.aika
Utils() - Constructor for class network.aika.Utils

V

value - Variable in class network.aika.neuron.activation.Activation.Builder
value - Variable in class network.aika.neuron.activation.Activation.State
valueOf(String) - Static method in enum network.aika.ActivationFunction: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.DistanceFunction: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.Activation.Mode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.Linker.Direction: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.Range.Mapping: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.Range.Operator: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.SearchNode.DebugState: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.activation.SearchNode.Decision: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.INeuron.LogicType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.INeuron.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.neuron.relation.InstanceRelation.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.Provider.SuspensionMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum network.aika.training.SynapseEvaluation.DeleteMode: Returns the enum constant of this type with the specified name.
ValueQueue() - Constructor for class network.aika.Document.ValueQueue
values() - Static method in enum network.aika.ActivationFunction: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.DistanceFunction: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.Activation.Mode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.Linker.Direction: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.Range.Mapping: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.Range.Operator: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.SearchNode.DebugState: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.activation.SearchNode.Decision: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.INeuron.LogicType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.INeuron.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.neuron.relation.InstanceRelation.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.Provider.SuspensionMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum network.aika.training.SynapseEvaluation.DeleteMode: Returns an array containing the constants of this enum type, in the order they are declared.
visited - Variable in class network.aika.lattice.Node.ThreadState
visited - Variable in class network.aika.lattice.NodeActivation
visitedCounter - Variable in class network.aika.Document
visitedCounter - Static variable in class network.aika.Model
vQueue - Variable in class network.aika.Document

W

weight - Variable in class network.aika.neuron.activation.Activation.State
weight - Variable in class network.aika.neuron.Synapse.Builder
weight - Variable in class network.aika.neuron.Synapse: The weight of this synapse.
WEIGHT_TOLERANCE - Static variable in class network.aika.neuron.INeuron
weightDelta - Variable in class network.aika.neuron.Synapse: The weight delta of this synapse.
Writable - Interface in network.aika
write(DataOutput) - Method in class network.aika.lattice.AndNode.Refinement
write(DataOutput) - Method in class network.aika.lattice.AndNode.RefValue
write(DataOutput) - Method in class network.aika.lattice.AndNode.RelationsMap
write(DataOutput) - Method in class network.aika.lattice.AndNode
write(DataOutput) - Method in class network.aika.lattice.InputNode
write(DataOutput) - Method in class network.aika.lattice.Node
write(DataOutput) - Method in class network.aika.lattice.OrNode.OrEntry
write(DataOutput) - Method in class network.aika.lattice.OrNode
write(DataOutput) - Method in class network.aika.neuron.activation.Range.Output
write(DataOutput) - Method in class network.aika.neuron.activation.Range.Relation
write(DataOutput) - Method in class network.aika.neuron.INeuron
write(DataOutput) - Method in class network.aika.neuron.relation.InstanceRelation
write(DataOutput) - Method in class network.aika.neuron.relation.RangeRelation
write(DataOutput) - Method in class network.aika.neuron.Synapse.Key
write(DataOutput) - Method in class network.aika.neuron.Synapse
write(DataOutput) - Method in interface network.aika.Writable: Serialize the fields of this object to out.

Z

ZERO - Static variable in class network.aika.neuron.activation.Activation.State

A B C D E F G H I K L M N O P Q R S T U V W Z