pascal.pl

 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