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fixes np.int64 bug in MaximumLikelihoodEstimation
This bug occurs because numpy does not take numpy.int64 to be an instance of int. For more details refer - numpy/numpy#2951
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3 files changed

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‎pgmpy/factors/Factor.py

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@@ -98,7 +98,7 @@ def __init__(self, variables, cardinality, values):
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values = np.array(values)
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if values.dtype != int and values.dtype != float:
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if all([values.dtype != value_type for value_type in (float, int, np.int64, np.float32)]):
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raise TypeError("Values: Expected type int or type float, got ", values.dtype)
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if len(cardinality) != len(variables):

‎test_bif.xml

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<BIF version="0.3">
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<NETWORK>
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<VARIABLE TYPE="nature">
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<NAME>bowel-problem</NAME>
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<OUTCOME>0</OUTCOME>
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<OUTCOME>1</OUTCOME>
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<PROPERTY>position = (190, 69)</PROPERTY>
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</VARIABLE>
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<VARIABLE TYPE="nature">
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<NAME>dog-out</NAME>
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<OUTCOME>0</OUTCOME>
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<OUTCOME>1</OUTCOME>
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<PROPERTY>position = (155, 165)</PROPERTY>
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</VARIABLE>
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<VARIABLE TYPE="nature">
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<NAME>family-out</NAME>
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<OUTCOME>0</OUTCOME>
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<OUTCOME>1</OUTCOME>
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<PROPERTY>position = (112, 69)</PROPERTY>
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</VARIABLE>
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<VARIABLE TYPE="nature">
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<NAME>hear-bark</NAME>
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<OUTCOME>0</OUTCOME>
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<OUTCOME>1</OUTCOME>
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<PROPERTY>position = (154, 241)</PROPERTY>
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</VARIABLE>
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<VARIABLE TYPE="nature">
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<NAME>light-on</NAME>
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<OUTCOME>0</OUTCOME>
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<OUTCOME>1</OUTCOME>
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<PROPERTY>position = (73, 165)</PROPERTY>
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</VARIABLE>
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<DEFINITION>
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<FOR>bowel-problem</FOR>
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<TABLE>0.01 0.99 </TABLE>
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</DEFINITION>
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<DEFINITION>
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<FOR>dog-out</FOR>
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<GIVEN>bowel-problem</GIVEN>
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<GIVEN>family-out</GIVEN>
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<TABLE>0.99 0.01 0.97 0.03 0.9 0.1 0.3 0.7 </TABLE>
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</DEFINITION>
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<DEFINITION>
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<FOR>family-out</FOR>
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<TABLE>0.15 0.85 </TABLE>
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</DEFINITION>
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<DEFINITION>
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<FOR>hear-bark</FOR>
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<GIVEN>dog-out</GIVEN>
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<TABLE>0.7 0.3 0.01 0.99 </TABLE>
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</DEFINITION>
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<DEFINITION>
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<FOR>light-on</FOR>
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<GIVEN>family-out</GIVEN>
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<TABLE>0.6 0.4 0.05 0.95 </TABLE>
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</DEFINITION>
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</NETWORK>
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</BIF>

‎test_xml.pgmx

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<ProbModelXML formatVersion="1.0">
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<ProbNet type="BayesianNetwork">
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<Variables>
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<Variable name="difficulty" role="Chance" type="FiniteState">
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<Comment />
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<Coordinates />
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<AdditionalProperties />
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<States>
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<State name="difficult">
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<AdditionalProperties />
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</State>
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<State name="easy">
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<AdditionalProperties />
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</State>
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</States>
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</Variable>
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<Variable name="intelligence" role="Chance" type="FiniteState">
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<Comment />
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<Coordinates />
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<AdditionalProperties />
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<States>
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<State name="dumb">
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<AdditionalProperties />
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</State>
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<State name="smart">
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<AdditionalProperties />
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</State>
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</States>
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</Variable>
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</Variables>
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<Links>
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<Link directed="1" var1="difficulty" var2="grade">
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<Comment>Directed Edge from difficulty to grade</Comment>
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<Label>diff_to_grad</Label>
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<AdditionalProperties />
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</Link>
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<Link directed="1" var1="grade" var2="recommendation_letter">
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<Comment>Directed Edge from grade to recommendation_letter</Comment>
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<Label>grad_to_reco</Label>
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<AdditionalProperties />
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</Link>
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<Link directed="1" var1="intelligence" var2="SAT">
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<Comment>Directed Edge from intelligence to SAT</Comment>
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<Label>intel_to_sat</Label>
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<AdditionalProperties />
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</Link>
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<Link directed="1" var1="intelligence" var2="grade">
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<Comment>Directed Edge from intelligence to grade</Comment>
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<Label>intel_to_grad</Label>
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<AdditionalProperties />
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</Link>
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</Links>
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<Potentials>
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<Potential role="Utility" type="Tree/ADD">
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<Variables>
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<Variable name="D0" />
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<Variable name="C0" />
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<Variable name="C1" />
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<Variable name="D1" />
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</Variables>
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<TopVariable name="D0" />
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<Branches>
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<Branch>
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<States>
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<State name="no" />
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</States>
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<Potential type="Tree/ADD">
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<TopVariable name="C1" />
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<Branches>
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<Branch>
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<Potential type="MixtureOfExponentials">
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<Variables>
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<Variable name="C0" />
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<Variable name="C1" />
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</Variables>
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<Subpotentials>
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<Potential type="Exponential">
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<Potential type="Table">
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<Values>3</Values>
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</Potential>
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</Potential>
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<Potential type="Exponential">
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<Coefficients>4 -1</Coefficients>
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<Potential type="Table">
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<Values>-1</Values>
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</Potential>
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<NumericVariables>
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<Variable name="C0" />
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<Variable name="C1" />
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</NumericVariables>
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</Potential>
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</Subpotentials>
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</Potential>
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<Thresholds>
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<Threshold value="-Infinity" />
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<Threshold belongsTo="Left" value="0" />
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</Thresholds>
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</Branch>
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<Branch>
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<Potential type="MixtureOfExponentials">
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<Variables>
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<Variable name="C1" />
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<Variable name="D1" />
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</Variables>
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<Subpotentials>
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<Potential type="Exponential">
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<Coefficients>0.25</Coefficients>
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<Potential type="Table">
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<Variables>
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<Variable name="D1" />
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</Variables>
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<Values>10 5</Values>
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</Potential>
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<NumericVariables>
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<Variable name="C1" />
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</NumericVariables>
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</Potential>
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</Subpotentials>
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</Potential>
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<Thresholds>
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<Threshold belongsTo="Left" value="0" />
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<Threshold value="+Infinity" />
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</Thresholds>
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</Branch>
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</Branches>
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</Potential>
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</Branch>
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<Branch>
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<States>
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<State name="yes" />
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</States>
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<Potential type="MixtureOfExponentials">
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<Variables>
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<Variable name="C0" />
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</Variables>
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<Subpotentials>
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<Potential type="Exponential">
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<Coefficients>1</Coefficients>
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<Potential type="Table">
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<Values>0.3</Values>
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</Potential>
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<NumericVariables>
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<Variable name="C0" />
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</NumericVariables>
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</Potential>
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<Potential type="Exponential">
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<Potential type="Table">
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<Values>0.7</Values>
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</Potential>
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</Potential>
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</Subpotentials>
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</Potential>
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</Branch>
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</Branches>
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</Potential>
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</Potentials>
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<AdditionalConstraints>
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<Constraint name="MaxNumParents">
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<Argument name="numParents" value="5" />
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</Constraint>
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</AdditionalConstraints>
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<Language>English</Language>
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<Comment>Student example model from Probabilistic Graphical Models: Principles and Techniques by Daphne Koller</Comment>
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</ProbNet>
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<AdditionalProperties>
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<Property name="elvira.title" value="X ray result" />
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</AdditionalProperties>
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<DecisionCriteria>
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<Criterion name="cost">
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<AdditionalProperties />
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</Criterion>
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<Criterion name="effectiveness">
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<AdditionalProperties />
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</Criterion>
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</DecisionCriteria>
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</ProbModelXML>

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