discrete bayesian network

This is an example input file for a Bayesian network with discrete conditional probability distributions. The example is a small (5 node) graph modeling a student’s performance. The graph skeleton data is also included, in the vertex set (“V”) and the edge set (“E”). The graph itself is from Koller et al. 53.:

{
    "V": ["Letter", "Grade", "Intelligence", "SAT", "Difficulty"],
    "E": [["Intelligence", "Grade"],
        ["Difficulty", "Grade"],
        ["Intelligence", "SAT"],
        ["Grade", "Letter"]],
    "Vdata": {
        "Letter": {
            "ord": 4,
            "numoutcomes": 2,
            "vals": ["weak", "strong"],
            "parents": ["Grade"],
            "children": None,
            "cprob": {
                "['A']": [.1, .9],
                "['B']": [.4, .6],
                "['C']": [.99, .01]
            }
        },

        "SAT": {
            "ord": 3,
            "numoutcomes": 2,
            "vals": ["lowscore", "highscore"],
            "parents": ["Intelligence"],
            "children": None,
            "cprob": {
                "['low']": [.95, .05],
                "['high']": [.2, .8]
            }
        },

        "Grade": {
            "ord": 2,
            "numoutcomes": 3,
            "vals": ["A", "B", "C"],
            "parents": ["Difficulty", "Intelligence"],
            "children": ["Letter"],
            "cprob": {
                "['easy', 'low']": [.3, .4, .3],
                "['easy', 'high']": [.9, .08, .02],
                "['hard', 'low']": [.05, .25, .7],
                "['hard', 'high']": [.5, .3, .2]
            }
        },

        "Intelligence": {
            "ord": 1,
            "numoutcomes": 2,
            "vals": ["low", "high"],
            "parents": None,
            "children": ["SAT", "Grade"],
            "cprob": [.7, .3]
        },

        "Difficulty": {
            "ord": 0,
            "numoutcomes": 2,
            "vals": ["easy", "hard"],
            "parents": None,
            "children": ["Grade"],
            "cprob":  [.6, .4]
        }
    }
}