cplint on SWISH -- Probabilistic Logic Programming

/* 
Registration dataset, it contains information about participants in a recent 
Seminar on Data Mining. 
We would like to find out what type of people attend the parties at the seminar.
From 
L. De Raedt, H. Blockeel, L. Dehaspe, and W. Van Laer. Three companions for data mining in first order logic. In S. Dzeroski and N. Lavrac, editors, Relational Data Mining, pages 105-139.  Springer-Verlag, 2001.

See also The ACE Data Mining System User's Manual
http://dtai.cs.kuleuven.be/ACE/doc/ACEuser-1.2.16.pdf

Downloaded from 
http://dtai.cs.kuleuven.be/static/ACE/doc/
*/

/** <examples>
?- induce_par([rand_train],P),test(P,[rand_test],LL,AUCROC,ROC,AUCPR,PR).
?- in(P),test(P,[all],LL,AUCROC,ROC,AUCPR,PR).
?- induce([all],P),test(P,[all],LL,AUCROC,ROC,AUCPR,PR).
*/

:-use_module(library(slipcover)).

:- if(current_predicate(use_rendering/1)).
:- use_rendering(c3).
:- use_rendering(lpad).
:- endif.

:-sc.

:- set_sc(depth_bound,false).
:- set_sc(neg_ex,given).
:- set_sc(megaex_bottom,7).
%:- set_sc(max_iter,2).
%:- set_sc(max_iter_structure,5).
:- set_sc(verbosity,1).

:- begin_bg.
company_info(jvt,commercial).
company_info(scuf,university).
company_info(ucro,university).
course(cso,2,introductory).
course(erm,3,introductory).
course(so2,4,introductory).
course(srw,3,advanced).

job(J):-
	participant(J, _, _, _).
company(C):-
	participant(_, C, _, _).

party_yes :- party(yes).
party_no :- party(no).

company_type(T):-
	company(C),
	company_info(C, T).

not_company_type(commercial):-
  \+ company_type(commercial).

not_company_type(university):-
  \+ company_type(university).

course_len(C, L):-
	course(C, L, _).
	
course_type(C, T):-
	course(C, _, T).

:- end_bg.

:- begin_in.
party(yes):0.5:-
  company_type(commercial).

party(no):0.5:-
  subscription(A),
  course_len(A,4),
  \+ company_type(commercial).
:- end_in.

fold(all,F):-
  findall(I,int(I),F).

fold(test,[adams,scott]).
fold(train,[blake, king, miller, turner]).

output(party/1).

input_cw(job/1).
input_cw(not_company_type/1).
input_cw(company_type/1).
input_cw(subscription/1).
input_cw(course_len/2).
input_cw(course_type/2).
input_cw(company/1).
input_cw(company_info/2).
input_cw(participant/4).
input_cw(course/3)/

determination(party/1,job/1).
determination(party/1,not_company_type/1).
determination(party/1,company_type/1).
determination(party/1,subscription/1).
determination(party/1,course_len/2).
determination(party/1,course_type/2).

%modeh(*,[party(yes),party(no)],
%  [party(yes),party(no)],
%  [job/1,company_type/1,subscription/1,course_len/2,course_type/2]).

modeh(*,party(yes)).
modeh(*,party(no)).

modeb(*,job(-#job)).
modeb(*,company_type(-#ctype)).
modeb(*,not_company_type(-#ctype)).
modeb(*,subscription(-sub)).
modeb(*,course_len(+sub,-#cl)).
modeb(*,course_type(+sub,-#ct)).

neg(party(M,yes)):- party(M,no).
neg(party(M,no)):- party(M,yes).

party(M,P):-
  participant(M,_, _, P, _).

begin(model(adams)).
participant(researcher,scuf,no,23).
subscription(erm).
subscription(so2).
subscription(srw).
end(model(adams)).

begin(model(blake)).
participant(president,jvt,yes,5).
subscription(cso).
subscription(erm).
end(model(blake)).

begin(model(king)).
participant(manager,ucro,no,78).
subscription(cso).
subscription(erm).
subscription(so2).
subscription(srw).
end(model(king)).

begin(model(miller)).
participant(manager,jvt,yes,14).
subscription(so2).
end(model(miller)).

begin(model(scott)).
participant(researcher,scuf,yes,94).
subscription(erm).
subscription(srw).
end(model(scott)).

begin(model(turner)).
participant(researcher,ucro,no,81).
subscription(so2).
subscription(srw).
end(model(turner)).

:- fold(all,F),
   sample(4,F,FTr,FTe),
   assert(fold(rand_train,FTr)),
   assert(fold(rand_test,FTe)).