Tutorials and notebooks
gum.config
1- Fundamental components
Arc
Edge
DiGraph
DAG
UndiGraph
CliqueGraph
MixedGraph
MixedGraph.addArc()
MixedGraph.addEdge()
MixedGraph.addNode()
MixedGraph.addNodeWithId()
MixedGraph.addNodes()
MixedGraph.adjacents()
MixedGraph.arcs()
MixedGraph.boundary()
MixedGraph.chainComponent()
MixedGraph.children()
MixedGraph.clear()
MixedGraph.connectedComponents()
MixedGraph.edges()
MixedGraph.empty()
MixedGraph.emptyArcs()
MixedGraph.emptyEdges()
MixedGraph.eraseArc()
MixedGraph.eraseChildren()
MixedGraph.eraseEdge()
MixedGraph.eraseNeighbours()
MixedGraph.eraseNode()
MixedGraph.eraseParents()
MixedGraph.existsArc()
MixedGraph.existsEdge()
MixedGraph.existsNode()
MixedGraph.hasDirectedPath()
MixedGraph.hasMixedOrientedPath()
MixedGraph.hasUndirectedCycle()
MixedGraph.mixedOrientedPath()
MixedGraph.mixedUnorientedPath()
MixedGraph.neighbours()
MixedGraph.nodes()
MixedGraph.nodes2ConnectedComponent()
MixedGraph.parents()
MixedGraph.partialUndiGraph()
MixedGraph.size()
MixedGraph.sizeArcs()
MixedGraph.sizeEdges()
MixedGraph.toDot()
MixedGraph.topologicalOrder()
PDAG
PDAG.addArc()
PDAG.addEdge()
PDAG.addNode()
PDAG.addNodeWithId()
PDAG.addNodes()
PDAG.adjacents()
PDAG.arcs()
PDAG.boundary()
PDAG.cSeparation()
PDAG.chainComponent()
PDAG.children()
PDAG.clear()
PDAG.connectedComponents()
PDAG.edges()
PDAG.empty()
PDAG.emptyArcs()
PDAG.emptyEdges()
PDAG.eraseArc()
PDAG.eraseChildren()
PDAG.eraseEdge()
PDAG.eraseNeighbours()
PDAG.eraseNode()
PDAG.eraseParents()
PDAG.existsArc()
PDAG.existsEdge()
PDAG.existsNode()
PDAG.hasDirectedPath()
PDAG.hasMixedOrientedPath()
PDAG.hasMixedReallyOrientedPath()
PDAG.hasUndirectedCycle()
PDAG.mixedOrientedPath()
PDAG.mixedUnorientedPath()
PDAG.moralGraph()
PDAG.moralizedAncestralGraph()
PDAG.neighbours()
PDAG.nodes()
PDAG.nodes2ConnectedComponent()
PDAG.parents()
PDAG.partialUndiGraph()
PDAG.size()
PDAG.sizeArcs()
PDAG.sizeEdges()
PDAG.toDot()
PDAG.topologicalOrder()
DiscreteVariable
DiscreteVariable.asDiscretizedVar()
DiscreteVariable.asIntegerVar()
DiscreteVariable.asLabelizedVar()
DiscreteVariable.asNumericalDiscreteVar()
DiscreteVariable.asRangeVar()
DiscreteVariable.description()
DiscreteVariable.domain()
DiscreteVariable.domainSize()
DiscreteVariable.empty()
DiscreteVariable.index()
DiscreteVariable.label()
DiscreteVariable.labels()
DiscreteVariable.name()
DiscreteVariable.numerical()
DiscreteVariable.setDescription()
DiscreteVariable.setName()
DiscreteVariable.stype()
DiscreteVariable.toDiscretizedVar()
DiscreteVariable.toIntegerVar()
DiscreteVariable.toLabelizedVar()
DiscreteVariable.toNumericalDiscreteVar()
DiscreteVariable.toRangeVar()
DiscreteVariable.toStringWithDescription()
DiscreteVariable.varType()
LabelizedVariable
DiscretizedVariable
IntegerVariable
RangeVariable
NumericalDiscreteVariable
Instantiation
Instantiation.add()
Instantiation.addVarsFromModel()
Instantiation.chgVal()
Instantiation.clear()
Instantiation.contains()
Instantiation.dec()
Instantiation.decIn()
Instantiation.decNotVar()
Instantiation.decOut()
Instantiation.decVar()
Instantiation.domainSize()
Instantiation.empty()
Instantiation.end()
Instantiation.erase()
Instantiation.fromdict()
Instantiation.hamming()
Instantiation.inOverflow()
Instantiation.inc()
Instantiation.incIn()
Instantiation.incNotVar()
Instantiation.incOut()
Instantiation.incVar()
Instantiation.isMutable()
Instantiation.nbrDim()
Instantiation.pos()
Instantiation.rend()
Instantiation.reorder()
Instantiation.setFirst()
Instantiation.setFirstIn()
Instantiation.setFirstNotVar()
Instantiation.setFirstOut()
Instantiation.setFirstVar()
Instantiation.setLast()
Instantiation.setLastIn()
Instantiation.setLastNotVar()
Instantiation.setLastOut()
Instantiation.setLastVar()
Instantiation.setMutable()
Instantiation.setVals()
Instantiation.todict()
Instantiation.unsetEnd()
Instantiation.unsetOverflow()
Instantiation.val()
Instantiation.variable()
Instantiation.variablesSequence()
Potential
Potential.KL()
Potential.abs()
Potential.add()
Potential.argmax()
Potential.argmin()
Potential.contains()
Potential.domainSize()
Potential.draw()
Potential.empty()
Potential.entropy()
Potential.extract()
Potential.fillWith()
Potential.fillWithFunction()
Potential.findAll()
Potential.get()
Potential.inverse()
Potential.isNonZeroMap()
Potential.log2()
Potential.loopIn()
Potential.margMaxIn()
Potential.margMaxOut()
Potential.margMinIn()
Potential.margMinOut()
Potential.margProdIn()
Potential.margProdOut()
Potential.margSumIn()
Potential.margSumOut()
Potential.max()
Potential.maxNonOne()
Potential.min()
Potential.minNonZero()
Potential.names
Potential.nbrDim()
Potential.newFactory()
Potential.new_abs()
Potential.new_log2()
Potential.new_sgn()
Potential.new_sq()
Potential.noising()
Potential.normalize()
Potential.normalizeAsCPT()
Potential.pos()
Potential.product()
Potential.putFirst()
Potential.random()
Potential.randomCPT()
Potential.randomDistribution()
Potential.remove()
Potential.reorganize()
Potential.scale()
Potential.set()
Potential.sgn()
Potential.shape
Potential.sq()
Potential.sum()
Potential.thisown
Potential.toarray()
Potential.toclipboard()
Potential.tolatex()
Potential.tolist()
Potential.topandas()
Potential.translate()
Potential.var_dims
Potential.var_names
Potential.variable()
Potential.variablesSequence()
2- Graphical Models
BayesNet
BayesNet.add()
BayesNet.addAMPLITUDE()
BayesNet.addAND()
BayesNet.addArc()
BayesNet.addArcs()
BayesNet.addCOUNT()
BayesNet.addEXISTS()
BayesNet.addFORALL()
BayesNet.addLogit()
BayesNet.addMAX()
BayesNet.addMEDIAN()
BayesNet.addMIN()
BayesNet.addNoisyAND()
BayesNet.addNoisyOR()
BayesNet.addNoisyORCompound()
BayesNet.addNoisyORNet()
BayesNet.addOR()
BayesNet.addSUM()
BayesNet.addStructureListener()
BayesNet.addVariables()
BayesNet.addWeightedArc()
BayesNet.ancestors()
BayesNet.arcs()
BayesNet.beginTopologyTransformation()
BayesNet.changePotential()
BayesNet.changeVariableLabel()
BayesNet.changeVariableName()
BayesNet.check()
BayesNet.children()
BayesNet.clear()
BayesNet.completeInstantiation()
BayesNet.connectedComponents()
BayesNet.cpt()
BayesNet.dag()
BayesNet.descendants()
BayesNet.dim()
BayesNet.empty()
BayesNet.endTopologyTransformation()
BayesNet.erase()
BayesNet.eraseArc()
BayesNet.exists()
BayesNet.existsArc()
BayesNet.family()
BayesNet.fastPrototype()
BayesNet.generateCPT()
BayesNet.generateCPTs()
BayesNet.hasSameStructure()
BayesNet.idFromName()
BayesNet.ids()
BayesNet.isIndependent()
BayesNet.jointProbability()
BayesNet.loadBIF()
BayesNet.loadBIFXML()
BayesNet.loadDSL()
BayesNet.loadNET()
BayesNet.loadO3PRM()
BayesNet.loadUAI()
BayesNet.loadXDSL()
BayesNet.log10DomainSize()
BayesNet.log2JointProbability()
BayesNet.maxNonOneParam()
BayesNet.maxParam()
BayesNet.maxVarDomainSize()
BayesNet.minNonZeroParam()
BayesNet.minParam()
BayesNet.minimalCondSet()
BayesNet.moralGraph()
BayesNet.moralizedAncestralGraph()
BayesNet.names()
BayesNet.nodeId()
BayesNet.nodes()
BayesNet.nodeset()
BayesNet.parents()
BayesNet.reverseArc()
BayesNet.saveBIF()
BayesNet.saveBIFXML()
BayesNet.saveDSL()
BayesNet.saveNET()
BayesNet.saveO3PRM()
BayesNet.saveUAI()
BayesNet.saveXDSL()
BayesNet.size()
BayesNet.sizeArcs()
BayesNet.thisown
BayesNet.toDot()
BayesNet.topologicalOrder()
BayesNet.variable()
BayesNet.variableFromName()
BayesNet.variableNodeMap()
BNGenerator
BNDatabaseGenerator
ExactBNdistance
GibbsBNdistance
JunctionTreeGenerator
EssentialGraph
MarkovBlanket
BayesNetFragment
BNLearner
BNLearner.G2()
BNLearner.addForbiddenArc()
BNLearner.addMandatoryArc()
BNLearner.addPossibleEdge()
BNLearner.chi2()
BNLearner.correctedMutualInformation()
BNLearner.currentTime()
BNLearner.databaseWeight()
BNLearner.domainSize()
BNLearner.epsilon()
BNLearner.eraseForbiddenArc()
BNLearner.eraseMandatoryArc()
BNLearner.erasePossibleEdge()
BNLearner.fitParameters()
BNLearner.getNumberOfThreads()
BNLearner.hasMissingValues()
BNLearner.history()
BNLearner.idFromName()
BNLearner.isGumNumberOfThreadsOverriden()
BNLearner.latentVariables()
BNLearner.learnBN()
BNLearner.learnDAG()
BNLearner.learnEssentialGraph()
BNLearner.learnMixedGraph()
BNLearner.learnPDAG()
BNLearner.learnParameters()
BNLearner.logLikelihood()
BNLearner.maxIter()
BNLearner.maxTime()
BNLearner.messageApproximationScheme()
BNLearner.minEpsilonRate()
BNLearner.mutualInformation()
BNLearner.nameFromId()
BNLearner.names()
BNLearner.nbCols()
BNLearner.nbRows()
BNLearner.nbrIterations()
BNLearner.periodSize()
BNLearner.pseudoCount()
BNLearner.rawPseudoCount()
BNLearner.recordWeight()
BNLearner.score()
BNLearner.setDatabaseWeight()
BNLearner.setEpsilon()
BNLearner.setForbiddenArcs()
BNLearner.setInitialDAG()
BNLearner.setMandatoryArcs()
BNLearner.setMaxIndegree()
BNLearner.setMaxIter()
BNLearner.setMaxTime()
BNLearner.setMinEpsilonRate()
BNLearner.setNumberOfThreads()
BNLearner.setPeriodSize()
BNLearner.setPossibleEdges()
BNLearner.setPossibleSkeleton()
BNLearner.setRecordWeight()
BNLearner.setSliceOrder()
BNLearner.setVerbosity()
BNLearner.state()
BNLearner.use3off2()
BNLearner.useAprioriBDeu()
BNLearner.useAprioriDirichlet()
BNLearner.useAprioriSmoothing()
BNLearner.useBDeuPrior()
BNLearner.useDirichletPrior()
BNLearner.useEM()
BNLearner.useGreedyHillClimbing()
BNLearner.useK2()
BNLearner.useLocalSearchWithTabuList()
BNLearner.useMDLCorrection()
BNLearner.useMIIC()
BNLearner.useNMLCorrection()
BNLearner.useNoApriori()
BNLearner.useNoCorrection()
BNLearner.useNoPrior()
BNLearner.useScoreAIC()
BNLearner.useScoreBD()
BNLearner.useScoreBDeu()
BNLearner.useScoreBIC()
BNLearner.useScoreK2()
BNLearner.useScoreLog2Likelihood()
BNLearner.useSmoothingPrior()
BNLearner.verbosity()
InfluenceDiagram
InfluenceDiagram.add()
InfluenceDiagram.addArc()
InfluenceDiagram.addArcs()
InfluenceDiagram.addChanceNode()
InfluenceDiagram.addDecisionNode()
InfluenceDiagram.addStructureListener()
InfluenceDiagram.addUtilityNode()
InfluenceDiagram.addVariables()
InfluenceDiagram.ancestors()
InfluenceDiagram.arcs()
InfluenceDiagram.chanceNodeSize()
InfluenceDiagram.changeVariableName()
InfluenceDiagram.children()
InfluenceDiagram.clear()
InfluenceDiagram.completeInstantiation()
InfluenceDiagram.connectedComponents()
InfluenceDiagram.cpt()
InfluenceDiagram.dag()
InfluenceDiagram.decisionNodeSize()
InfluenceDiagram.decisionOrder()
InfluenceDiagram.decisionOrderExists()
InfluenceDiagram.descendants()
InfluenceDiagram.empty()
InfluenceDiagram.erase()
InfluenceDiagram.eraseArc()
InfluenceDiagram.exists()
InfluenceDiagram.existsArc()
InfluenceDiagram.existsPathBetween()
InfluenceDiagram.family()
InfluenceDiagram.fastPrototype()
InfluenceDiagram.getDecisionGraph()
InfluenceDiagram.hasSameStructure()
InfluenceDiagram.idFromName()
InfluenceDiagram.ids()
InfluenceDiagram.isChanceNode()
InfluenceDiagram.isDecisionNode()
InfluenceDiagram.isIndependent()
InfluenceDiagram.isUtilityNode()
InfluenceDiagram.loadBIFXML()
InfluenceDiagram.log10DomainSize()
InfluenceDiagram.moralGraph()
InfluenceDiagram.moralizedAncestralGraph()
InfluenceDiagram.names()
InfluenceDiagram.nodeId()
InfluenceDiagram.nodes()
InfluenceDiagram.nodeset()
InfluenceDiagram.parents()
InfluenceDiagram.saveBIFXML()
InfluenceDiagram.size()
InfluenceDiagram.sizeArcs()
InfluenceDiagram.thisown
InfluenceDiagram.toDot()
InfluenceDiagram.topologicalOrder()
InfluenceDiagram.utility()
InfluenceDiagram.utilityNodeSize()
InfluenceDiagram.variable()
InfluenceDiagram.variableFromName()
InfluenceDiagram.variableNodeMap()
ShaferShenoyLIMIDInference
ShaferShenoyLIMIDInference.MEU()
ShaferShenoyLIMIDInference.addEvidence()
ShaferShenoyLIMIDInference.addNoForgettingAssumption()
ShaferShenoyLIMIDInference.chgEvidence()
ShaferShenoyLIMIDInference.clear()
ShaferShenoyLIMIDInference.eraseAllEvidence()
ShaferShenoyLIMIDInference.eraseEvidence()
ShaferShenoyLIMIDInference.hardEvidenceNodes()
ShaferShenoyLIMIDInference.hasEvidence()
ShaferShenoyLIMIDInference.hasHardEvidence()
ShaferShenoyLIMIDInference.hasNoForgettingAssumption()
ShaferShenoyLIMIDInference.hasSoftEvidence()
ShaferShenoyLIMIDInference.influenceDiagram()
ShaferShenoyLIMIDInference.isSolvable()
ShaferShenoyLIMIDInference.junctionTree()
ShaferShenoyLIMIDInference.makeInference()
ShaferShenoyLIMIDInference.meanVar()
ShaferShenoyLIMIDInference.nbrEvidence()
ShaferShenoyLIMIDInference.nbrHardEvidence()
ShaferShenoyLIMIDInference.nbrSoftEvidence()
ShaferShenoyLIMIDInference.optimalDecision()
ShaferShenoyLIMIDInference.posterior()
ShaferShenoyLIMIDInference.posteriorUtility()
ShaferShenoyLIMIDInference.reducedGraph()
ShaferShenoyLIMIDInference.reducedLIMID()
ShaferShenoyLIMIDInference.reversePartialOrder()
ShaferShenoyLIMIDInference.setEvidence()
ShaferShenoyLIMIDInference.softEvidenceNodes()
ShaferShenoyLIMIDInference.updateEvidence()
CredalNet
CredalNet.NodeType_Credal
CredalNet.NodeType_Indic
CredalNet.NodeType_Precise
CredalNet.NodeType_Vacuous
CredalNet.addArc()
CredalNet.addVariable()
CredalNet.approximatedBinarization()
CredalNet.bnToCredal()
CredalNet.computeBinaryCPTMinMax()
CredalNet.credalNet_currentCpt()
CredalNet.credalNet_srcCpt()
CredalNet.currentNodeType()
CredalNet.current_bn()
CredalNet.domainSize()
CredalNet.epsilonMax()
CredalNet.epsilonMean()
CredalNet.epsilonMin()
CredalNet.fillConstraint()
CredalNet.fillConstraints()
CredalNet.get_binaryCPT_max()
CredalNet.get_binaryCPT_min()
CredalNet.hasComputedBinaryCPTMinMax()
CredalNet.idmLearning()
CredalNet.instantiation()
CredalNet.intervalToCredal()
CredalNet.intervalToCredalWithFiles()
CredalNet.isSeparatelySpecified()
CredalNet.lagrangeNormalization()
CredalNet.nodeType()
CredalNet.saveBNsMinMax()
CredalNet.setCPT()
CredalNet.setCPTs()
CredalNet.src_bn()
CNMonteCarloSampling
CNMonteCarloSampling.CN()
CNMonteCarloSampling.currentTime()
CNMonteCarloSampling.dynamicExpMax()
CNMonteCarloSampling.dynamicExpMin()
CNMonteCarloSampling.epsilon()
CNMonteCarloSampling.history()
CNMonteCarloSampling.insertEvidenceFile()
CNMonteCarloSampling.insertModalsFile()
CNMonteCarloSampling.makeInference()
CNMonteCarloSampling.marginalMax()
CNMonteCarloSampling.marginalMin()
CNMonteCarloSampling.maxIter()
CNMonteCarloSampling.maxTime()
CNMonteCarloSampling.messageApproximationScheme()
CNMonteCarloSampling.minEpsilonRate()
CNMonteCarloSampling.nbrIterations()
CNMonteCarloSampling.periodSize()
CNMonteCarloSampling.setEpsilon()
CNMonteCarloSampling.setMaxIter()
CNMonteCarloSampling.setMaxTime()
CNMonteCarloSampling.setMinEpsilonRate()
CNMonteCarloSampling.setPeriodSize()
CNMonteCarloSampling.setRepetitiveInd()
CNMonteCarloSampling.setVerbosity()
CNMonteCarloSampling.verbosity()
CNLoopyPropagation
CNLoopyPropagation.CN()
CNLoopyPropagation.InferenceType_nodeToNeighbours
CNLoopyPropagation.InferenceType_ordered
CNLoopyPropagation.InferenceType_randomOrder
CNLoopyPropagation.currentTime()
CNLoopyPropagation.dynamicExpMax()
CNLoopyPropagation.dynamicExpMin()
CNLoopyPropagation.epsilon()
CNLoopyPropagation.eraseAllEvidence()
CNLoopyPropagation.history()
CNLoopyPropagation.inferenceType()
CNLoopyPropagation.insertEvidenceFile()
CNLoopyPropagation.insertModalsFile()
CNLoopyPropagation.makeInference()
CNLoopyPropagation.marginalMax()
CNLoopyPropagation.marginalMin()
CNLoopyPropagation.maxIter()
CNLoopyPropagation.maxTime()
CNLoopyPropagation.messageApproximationScheme()
CNLoopyPropagation.minEpsilonRate()
CNLoopyPropagation.nbrIterations()
CNLoopyPropagation.periodSize()
CNLoopyPropagation.saveInference()
CNLoopyPropagation.setEpsilon()
CNLoopyPropagation.setMaxIter()
CNLoopyPropagation.setMaxTime()
CNLoopyPropagation.setMinEpsilonRate()
CNLoopyPropagation.setPeriodSize()
CNLoopyPropagation.setRepetitiveInd()
CNLoopyPropagation.setVerbosity()
CNLoopyPropagation.thisown
CNLoopyPropagation.verbosity()
MarkovRandomField
MarkovRandomField.add()
MarkovRandomField.addFactor()
MarkovRandomField.addStructureListener()
MarkovRandomField.addVariables()
MarkovRandomField.beginTopologyTransformation()
MarkovRandomField.changeVariableLabel()
MarkovRandomField.changeVariableName()
MarkovRandomField.clear()
MarkovRandomField.completeInstantiation()
MarkovRandomField.connectedComponents()
MarkovRandomField.dim()
MarkovRandomField.edges()
MarkovRandomField.empty()
MarkovRandomField.endTopologyTransformation()
MarkovRandomField.erase()
MarkovRandomField.eraseFactor()
MarkovRandomField.exists()
MarkovRandomField.existsEdge()
MarkovRandomField.factor()
MarkovRandomField.factors()
MarkovRandomField.fastPrototype()
MarkovRandomField.fromBN()
MarkovRandomField.generateFactor()
MarkovRandomField.generateFactors()
MarkovRandomField.graph()
MarkovRandomField.hasSameStructure()
MarkovRandomField.idFromName()
MarkovRandomField.ids()
MarkovRandomField.isIndependent()
MarkovRandomField.loadUAI()
MarkovRandomField.log10DomainSize()
MarkovRandomField.maxNonOneParam()
MarkovRandomField.maxParam()
MarkovRandomField.maxVarDomainSize()
MarkovRandomField.minNonZeroParam()
MarkovRandomField.minParam()
MarkovRandomField.minimalCondSet()
MarkovRandomField.names()
MarkovRandomField.neighbours()
MarkovRandomField.nodeId()
MarkovRandomField.nodes()
MarkovRandomField.nodeset()
MarkovRandomField.saveUAI()
MarkovRandomField.size()
MarkovRandomField.sizeEdges()
MarkovRandomField.smallestFactorFromNode()
MarkovRandomField.thisown
MarkovRandomField.toDot()
MarkovRandomField.toDotAsFactorGraph()
MarkovRandomField.variable()
MarkovRandomField.variableFromName()
MarkovRandomField.variableNodeMap()
ShaferShenoyMRFInference
PRMexplorer
PRMexplorer.aggType
PRMexplorer.classAggregates()
PRMexplorer.classAttributes()
PRMexplorer.classDag()
PRMexplorer.classImplements()
PRMexplorer.classParameters()
PRMexplorer.classReferences()
PRMexplorer.classSlotChains()
PRMexplorer.classes()
PRMexplorer.cpf()
PRMexplorer.getDirectSubClass()
PRMexplorer.getDirectSubInterfaces()
PRMexplorer.getDirectSubTypes()
PRMexplorer.getImplementations()
PRMexplorer.getLabelMap()
PRMexplorer.getLabels()
PRMexplorer.getSuperClass()
PRMexplorer.getSuperInterface()
PRMexplorer.getSuperType()
PRMexplorer.getalltheSystems()
PRMexplorer.interAttributes()
PRMexplorer.interReferences()
PRMexplorer.interfaces()
PRMexplorer.isAttribute()
PRMexplorer.isClass()
PRMexplorer.isInterface()
PRMexplorer.isType()
PRMexplorer.load()
PRMexplorer.types()
3- Causality
4- scikit-learn-like BN Classifiers
5- pyAgrum.lib modules
6- Miscellaneous
7- Customizing pyAgrum
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