• Introduction
  • Licensing
  • What's new in SMILE 2
  • Platforms and wrappers
    • Python and PySMILE
    • Java and jSMILE
      • Maven
    • .NET and SMILE.NET
    • R and rSMILE
  • Hello, SMILE Wrapper!
    • Success/Forecast model
    • VentureBN.xdsl
    • The program
      • Hello.py
      • Hello.java
      • Hello.cs
      • Hello.R
  • Using SMILE Wrappers
    • Error handling
    • Identifiers
    • Networks, nodes and arcs
      • Network
      • Nodes
        • Node types
        • Creating and deleting nodes
        • Iterating over nodes
        • Node definition
        • Node value
        • Node evidence
        • Other node attributes
      • Arcs
    • Multidimensional arrays
    • Input and output
    • Inference
      • Target nodes
      • Noisy-MAX decomposition
      • Probability of evidence
      • Annealed MAP
      • Most probable explanation
    • Case manager
    • User properties
    • Submodels
    • Discrete nodes and numeric domains
      • Outcome intervals
      • Outcome point values
    • Canonical nodes
      • Noisy-MAX
      • Noisy-Adder
    • Influence diagrams
    • Dynamic Bayesian networks
      • Temporal node types
      • Temporal arcs
      • Unrolling
      • Temporal definitions
      • Temporal evidence
      • Temporal beliefs
    • Continuous models
      • Equation-based nodes
      • Continuous evidence
      • Continuous inference
    • Hybrid models
    • Diagnosis
      • Diagnostic roles
      • Observation cost
      • Diagnostic session
      • Distance and entropy-based measures
    • Learning
      • Learning network structure
      • Learning network parameters
      • Validation
  • Tutorials
    • Tutorial 1: Creating a Bayesian Network
      • Tutorial1.py
      • Tutorial1.java
      • Tutorial1.cs
      • Tutorial1.R
    • Tutorial 2: Inference with a Bayesian Network
      • Tutorial2.py
      • Tutorial2.java
      • Tutorial2.cs
      • Tutorial2.R
    • Tutorial 3: Exploring the contents of a model
      • Tutorial3.py
      • Tutorial3.java
      • Tutorial3.cs
      • Tutorial3.R
    • Tutorial 4: Creating the Influence Diagram
      • Tutorial4.py
      • Tutorial4.java
      • Tutorial4.cs
      • Tutorial4.R
    • Tutorial 5: Inference in an Influence Diagram
      • Tutorial5.py
      • Tutorial5.java
      • Tutorial5.cs
      • Tutorial5.R
    • Tutorial 6: Dynamic model
      • Tutorial6.py
      • Tutorial6.java
      • Tutorial6.cs
      • Tutorial6.R
    • Tutorial 7: Continuous model
      • Tutorial7.py
      • Tutorial7.java
      • Tutorial7.cs
      • Tutorial7.R
    • Tutorial 8: Hybrid model
      • Tutorial8.py
      • Tutorial8.java
      • Tutorial8.cs
      • Tutorial8.R
    • Tutorial 9: Diagnosis
      • Tutorial9.py
      • Tutorial9.java
      • Tutorial9.cs
      • Tutorial9.R
    • Tutorial 10: Structure learning
      • Tutorial10.py
      • Tutorial10.java
      • Tutorial10.cs
      • Tutorial10.R
  • Equations reference
    • Operators
    • Random Number Generators
    • Statistical Functions
    • Arithmetic Functions
    • Combinatoric Functions
    • Trigonometric Functions
    • Hyperbolic Functions
    • Logical/Conditional functions
    • Custom Functions
  • PySMILE reference
    • pysmile.AnnealedMapResults
    • pysmile.AnnealedMapTuning
    • pysmile.BayesianAlgorithmType
    • pysmile.CaseEvidenceInfo
    • pysmile.CaseEvidenceType
    • pysmile.DeMorganParentType
    • pysmile.DiagNetwork
    • pysmile.DiagResults
    • pysmile.DiscretizationInterval
    • pysmile.DocItemInfo
    • pysmile.EPISParams
    • pysmile.FaultInfo
    • pysmile.InfluenceDiagramAlgorithmType
    • pysmile.License
    • pysmile.MpeResults
    • pysmile.MultiFaultAlgorithmType
    • pysmile.Network
    • pysmile.NodeSensitivity
    • pysmile.NodeTemporalType
    • pysmile.NodeType
    • pysmile.ObservationInfo
    • pysmile.SMILEException
    • pysmile.SensitivityResults
    • pysmile.SingleFaultAlgorithmType
    • pysmile.TemporalInfo
    • pysmile.UnrollResults
    • pysmile.UserProperty
    • pysmile.ValueOfInfo
    • Learning
      • pysmile.learning.BayesianSearch
      • pysmile.learning.BkKnowledge
      • pysmile.learning.Curve
      • pysmile.learning.DataMatch
      • pysmile.learning.DataSet
      • pysmile.learning.EM
      • pysmile.learning.GreedyThickThinning
      • pysmile.learning.NaiveBayes
      • pysmile.learning.PC
      • pysmile.learning.Pattern
      • pysmile.learning.TAN
      • pysmile.learning.Validator
  • Acknowledgments