I- input symbol type
public class BlueFringeEDSMDFA<I> extends BlueFringeRPNIDFA<I>
BlueFringeRPNIDFAalgorithm. However, whereas the basic RPNI approach merges the very first pair of nodes that resemble a valid merge, the EDSM variant prioritizes the promotion of states (to be unmergable) and only proceeds to merge states, if there exists at least one mergable blue state for every red state. If such a situation occurs, the algorithm merges the two states whose merge would yield the biggest score (see
EDSMUtil.score(UniversalDeterministicAutomaton, List, List)). Thus the behavior of this algorithm is more passive, or as the name suggest evidence-driven.
PassiveLearningAlgorithm.PassiveAcceptorLearner<M extends net.automatalib.automata.fsa.FiniteStateAcceptor<?,I>,I>, PassiveLearningAlgorithm.PassiveDFALearner<I>, PassiveLearningAlgorithm.PassiveMealyLearner<I,O>, PassiveLearningAlgorithm.PassiveNFALearner<I>
|Constructor and Description|
|Modifier and Type||Method and Description|
addSamples, initializePTA, ptaToModel
decideOnValidMerge, setDeterministic, setParallel, tryMerge
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
addNegativeSample, addNegativeSamples, addNegativeSamples, addPositiveSample, addPositiveSamples, addPositiveSamples
public BlueFringeEDSMDFA(net.automatalib.words.Alphabet<I> alphabet)
alphabet- the alphabet
public net.automatalib.automata.fsa.DFA<?,I> computeModel()
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