5
GeNIe Modeler
Version 2.3.R4, Built on 2/27/2019
Table of Contents
Exact algorithms ......................................................................................................................................... 2365.7.6.1
Clustering algorithm ............................................................................................................................ 236
5.7.6.1.1
Relevance-based decomposition ....................................................................................................... 238
5.7.6.1.2
Polytree algorithm ................................................................................................................................ 238
5.7.6.1.3
Stochastic sampling algorithms .............................................................................................................. 2395.7.6.2
Probabilistic Logic Sampling ............................................................................................................. 239
5.7.6.2.1
Likelihood Sampling ............................................................................................................................. 239
5.7.6.2.2
Backward Sampling .............................................................................................................................. 239
5.7.6.2.3
AIS algorithm ......................................................................................................................................... 239
5.7.6.2.4
EPIS Sampling ........................................................................................................................................ 240
5.7.6.2.5
Special algorithms ..................................................................................................................................... 2415.7.6.3
Probability of evidence ....................................................................................................................... 241
5.7.6.3.1
Annealed MAP ....................................................................................................................................... 245
5.7.6.3.2
Influence diagrams algorithms ................................................................................. 2525.7.7
Policy evaluation ........................................................................................................................................ 2525.7.7.1
Find Best Policy ........................................................................................................................................... 2535.7.7.2
Algorithms for continuous and hybrid models .......................................................... 2545.7.8
Introduction ................................................................................................................................................. 2545.7.8.1
Autodiscretization ...................................................................................................................................... 2555.7.8.2
Hybrid Forward Sampling ......................................................................................................................... 2585.7.8.3
5.8 Obfuscation ..................................................................................................................... 259
5.9 Program options ............................................................................................................. 265
5.10 Keyboard shortcuts ......................................................................................................... 271
6. Using GeNIe
275
6.1 Introduction .................................................................................................................... 276
6.2 Bayesian networks .......................................................................................................... 276
Building a Bayesian network ..................................................................................... 2766.2.1
Useful structural transformations ............................................................................. 2766.2.2
Entering and retracting evidence .............................................................................. 2826.2.3
Virtual evidence ........................................................................................................ 2876.2.4
Viewing results .......................................................................................................... 2906.2.5
Strength of influences ............................................................................................... 2976.2.6
Controlling values ..................................................................................................... 3046.2.7
Sensitivity analysis in Bayesian networks ................................................................ 3076.2.8
6.3 Influence diagrams .......................................................................................................... 314
Building an influence diagram .................................................................................. 3146.3.1
Viewing results .......................................................................................................... 3226.3.2
Sensitivity analysis in influence diagrams ................................................................ 3236.3.3
Value of information ................................................................................................. 3286.3.4
6.4 Support for diagnosis ..................................................................................................... 335
Introduction ............................................................................................................... 3356.4.1
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