- test_pascal(:T:probabilistic_program, +TestFolds:list_of_atoms, -LL:float, -AUCROC:float, -ROC:dict, -AUCPR:float, -PR:dict) is det
- The predicate takes as input in T a probabilistic constraint logic theory,
tests T on the folds indicated in TestFolds and returns the
log likelihood of the test examples in LL, the area under the Receiver
Operating Characteristic curve in AUCROC, a dict containing the points
of the ROC curve in ROC, the area under the Precision Recall curve in AUCPR
and a dict containing the points of the PR curve in PR
- test_prob_pascal(:T:probabilistic_program, +TestFolds:list_of_atoms, -NPos:int, -NNeg:int, -LL:float, -Results:list) is det
- The predicate takes as input in T a probabilistic constraint logic theory,
tests T on the folds indicated in TestFolds and returns
the number of positive examples in NPos, the number of negative examples
in NNeg, the log likelihood in LL
and in Results a list containing the probabilistic result for each query contained in TestFolds.
- induce_pascal(:TrainFolds:list_of_atoms, -T:probabilistic_theory) is det
- The predicate performs structure learning using the folds indicated in
TrainFolds for training.
It returns in T the learned probabilistic constraint logic theory.
- induce_par_pascal(:TrainFolds:list_of_atoms, -T:probabilistic_program) is det
- The predicate learns the parameters of the theory stored in begin_in/end_in
section of the input file using the folds indicated in TrainFolds for training.
It returns in T the input theory with the updated parameters.
- set_pascal(:Parameter:atom, +Value:term) is det
- The predicate sets the value of a parameter
For a list of parameters see
https://github.com/friguzzi/pascal/blob/master/doc/manual.pdf or
- setting_pascal(:Parameter:atom, -Value:term) is det
- The predicate returns the value of a parameter
For a list of parameters see
https://github.com/friguzzi/pascal/blob/master/doc/manual.pdf or
