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Currently, h = model.fit(learning_problem=lp).best_hypotheses() returns an OWLClassExpression.
It would be useful to add a new argument to the fit method, e.g., return_info or verbose. If the latter evaluates to True, then fit returns a tuple: h, info = model.fit(learning_problem=lp, .best_hypotheses()). The returned info can be a list or dictionary containing at least the quality of the computed solution(s).
h = model.fit(learning_problem=lp).best_hypotheses()returns an OWLClassExpression.fitmethod, e.g.,return_infoorverbose. If the latter evaluates to True, thenfitreturns a tuple:h, info = model.fit(learning_problem=lp, .best_hypotheses()). The returnedinfocan be alistordictionarycontaining at least the quality of the computed solution(s).