• Introduction
• Licensing
• What's new in SMILE 2
• Compiler and linker options
  • Visual C++
  • gcc and clang
• Hello, SMILE!
  • Success/Forecast model
  • The program
  • hello.cpp
  • VentureBN.xdsl
• Using SMILE
  • Main header file
  • Error handling
  • Multithreading
  • Unicode support
  • Naming conventions and identifiers
  • Arrays
  • Networks, nodes and arcs
    • Network
    • Nodes
    • Arcs
  • Anatomy of a node
    • Multidimensional arrays
    • Node definition
    • Node value & evidence
    • Other node attributes
  • Discrete Bayesian networks
    • CPT nodes
    • Canonical nodes
      • Noisy-MAX
      • Noisy-Adder
    • Discrete deterministic nodes
    • Discrete nodes and numeric domains
      • Outcome intervals
      • Outcome point values
  • Qualitative models
  • Influence diagrams
  • Dynamic Bayesian networks
    • Unrolling
    • Temporal definitions
    • Temporal evidence
    • Temporal beliefs
  • Continuous models
    • Equation-based nodes
    • Continuous inference
  • Hybrid models
  • Input and output
  • Inference
  • User properties
  • Cases
  • Diagnosis
    • Diagnostic roles
    • Observation cost
    • Diagnostic session
    • Distance and entropy-based measures
  • Sensitivity analysis
  • Datasets
    • Text file I/O
    • Discrete and continuous variables
    • Generating data from a network
    • Discretization
  • Learning
    • Learning network structure
    • Learning network parameters
    • Validation
• Tutorials
  • main.cpp
  • Tutorial 1: Creating a Bayesian Network
    • tutorial1.cpp
  • Tutorial 2: Inference with a Bayesian Network
    • tutorial2.cpp
  • Tutorial 3: Exploring the contents of a model
    • tutorial3.cpp
  • Tutorial 4: Creating an Influence Diagram
    • tutorial4.cpp
  • Tutorial 5: Inference in an Influence Diagram
    • tutorial5.cpp
  • Tutorial 6: A dynamic model
    • tutorial6.cpp
  • Tutorial 7: A continuous model
    • tutorial7.cpp
  • Tutorial 8: Hybrid model
    • tutorial8.cpp
  • Tutorial 9: Structure learning
    • tutorial9.cpp
• Reference Manual
  • Node types
  • Error codes
  • Arrays and matrices
    • DSL_stringArray
    • DSL_idArray
    • DSL_numArray
    • DSL_intArray
    • DSL_doubleArray
    • DSL_Dmatrix
  • DSL_network
  • DSL_node
  • Node definitions
    • DSL_nodeDef
    • DSL_discDef
    • DSL_cpt
    • DSL_truthTable
    • DSL_lazyDef
    • DSL_qualDef
    • DSL_demorgan
    • DSL_ciDef
    • DSL_noisyMAX
    • DSL_noisyAdder
    • DSL_decision
    • DSL_utility
    • DSL_mau
    • DSL_equation
  • Node values
    • DSL_nodeVal
    • DSL_discVal
    • DSL_beliefVector
    • DSL_policyValues
    • DSL_expectedUtility
    • DSL_mauExpectedUtility
    • DSL_equationEvaluation
  • DSL_userProperties
  • DSL_generalEquation
  • DSL_instanceCounts
  • DSL_dataset
  • DSL_dataGenerator
  • DSL_validator
  • DSL_progress
  • DSL_diagSession
  • DSL_sensitivity
  • Learning
    • DSL_em
    • DSL_bs
    • DSL_pc
    • DSL_tan
    • DSL_abn
    • DSL_nb
    • DSL_bkgndKnowledge
    • DSL_bsEvaluator
    • DSL_pattern
  • Equations
    • Operators
    • Random Number Generators
    • Statistical Functions
    • Arithmetic Functions
    • Combinatoric Functions
    • Trigonometric Functions
    • Hyperbolic Functions
    • Logical/Conditional functions
    • Custom Functions
  • Global functions
• Appendix M: Matlab and SMILE
  • matsmile.cpp
• Acknowledgments