Information Theory of Bayesian network
- class pyAgrum.InformationTheory(*args)
This class gathers information theory concepts for subsets named X,Y and Z computed with only one inference.
- Parameters:
nodeset (- Z (intstr or iterable[intstr] ) -- a third (an optional)) –
nodeset –
nodeset –
- entropyX()
- Returns:
The entropy of nodeset X.
- Return type:
float
- entropyXY()
- Return type:
float- Returns:
- float
The entropy of nodeset, union of X and Y.
- entropyXYgivenZ()
- Return type:
float
- entropyXgivenY()
- Return type:
float- Returns:
- float
The conditional entropy of nodeset X conditionned by nodeset Y
- entropyY()
- Return type:
float- Returns:
- float
The entropy of nodeset X.
- entropyYgivenX()
- Return type:
float- Returns:
- float
The conditional entropy of nodeset Y conditionned by nodeset X
- mutualInformationXY()
- Return type:
float
- mutualInformationXYgivenZ()
- Return type:
float- Returns:
- float
The conditional mutual information between nodeset X and nodeset Y conditionned by nodeset Z
- variationOfInformationXY()
- Return type:
float- Returns:
- float
The variation of information between nodeset X and nodeset Y