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start with pfl learning.

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This commit is contained in:
Vitor Santos Costa
2012-06-22 19:00:12 +01:00
parent 5fe052a3ef
commit 87e0b67e76
10 changed files with 141 additions and 14 deletions
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51
packages/CLPBN/learning/em.yap
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@@ -76,15 +76,21 @@ handle_em(error(repeated_parents)) :-
% and more detailed info on distributions, namely with a list of all instances for the distribution.
init_em(Items, state( AllDists, AllDistInstances, MargVars, SolverVars)) :-
clpbn_flag(em_solver, Solver),
% only used for PCGs
clpbn_init_graph(Solver),
% create the ground network
call_run_all(Items),
% randomise_all_dists,
% set initial values for distributions
uniformise_all_dists,
% get all variablews to marginalise
attributes:all_attvars(AllVars0),
% and order them
sort_vars_by_key(AllVars0,AllVars,[]),
% remove variables that do not have to do with this query.
% check_for_hidden_vars(AllVars1, AllVars1, AllVars),
different_dists(AllVars, AllDists, AllDistInstances, MargVars),
% setup solver by doing parameter independent work.
clpbn_init_solver(Solver, MargVars, AllVars, _, SolverVars).
% loop for as long as you want.
@@ -116,15 +122,32 @@ ltables([Id-T|Tables], [Key-LTable|FTables]) :-
% collect the different dists we are going to learn next.
different_dists(AllVars, AllDists, AllInfo, MargVars) :-
all_dists(AllVars, Dists0),
all_dists(AllVars, AllVars, Dists0),
sort(Dists0, Dists1),
group(Dists1, AllDists, AllInfo, MargVars0, []),
sort(MargVars0, MargVars).
all_dists([], []).
all_dists([V|AllVars], [i(Id, [V|Parents], Cases, Hiddens)|Dists]) :-
%
% V -> to Id defining V. We get:
% the random variables that are parents
% the cases that can happen, eg if we have A <- B, C
% A and B are boolean w/o evidence, and C is f, the cases could be
% [0,0,1], [0,1,1], [1,0,0], [1,1,0],
% Hiddens will be C
%
all_dists([], _, []).
all_dists([V|AllVars], AllVars0, [i(Id, [V|Parents], Cases, Hiddens)|Dists]) :-
clpbn:use_parfactors(on), !,
clpbn:get_atts(V, [key(K)]),
pfl:factor(bayes,Id,[K|PKeys],_,_,_),
find_variables(PKeys, AllVars0, Parents),
generate_hidden_cases([V|Parents], CompactCases, Hiddens),
uncompact_cases(CompactCases, Cases),
all_dists(AllVars, AllVars0, Dists).
all_dists([V|AllVars], AllVars0, [i(Id, [V|Parents], Cases, Hiddens)|Dists]) :-
% V is an instance of Id
clpbn:get_atts(V, [dist(Id,Parents)]),
sort([V|Parents], Sorted),
sort([V|Parents], Sorted),
length(Sorted, LengSorted),
length(Parents, LengParents),
(
@@ -133,15 +156,31 @@ all_dists([V|AllVars], [i(Id, [V|Parents], Cases, Hiddens)|Dists]) :-
true
;
throw(error(repeated_parents))
),
),
generate_hidden_cases([V|Parents], CompactCases, Hiddens),
uncompact_cases(CompactCases, Cases),
all_dists(AllVars, Dists).
all_dists(AllVars, AllVars0, Dists).
find_variables([], _AllVars0, []).
find_variables([K|PKeys], AllVars0, [Parent|Parents]) :-
find_variable(K, AllVars0, Parent),
find_variables(PKeys, AllVars0, Parents).
find_variable(K, [Parent|_AllVars0], Parent) :-
clpbn:get_atts(Parent, [key(K0)]), K0 =@= K, !.
find_variable(K, [_|AllVars0], Parent) :-
find_variable(K, AllVars0, Parent).
generate_hidden_cases([], [], []).
generate_hidden_cases([V|Parents], [P|Cases], Hiddens) :-
clpbn:get_atts(V, [evidence(P)]), !,
generate_hidden_cases(Parents, Cases, Hiddens).
generate_hidden_cases([V|Parents], [Cases|MoreCases], [V|Hiddens]) :-
clpbn:use_parfactors(on), !,
clpbn:get_atts(V, [key(K)]),
pfl:skolem(K,D), length(D,Sz),
gen_cases(0, Sz, Cases),
generate_hidden_cases(Parents, MoreCases, Hiddens).
generate_hidden_cases([V|Parents], [Cases|MoreCases], [V|Hiddens]) :-
clpbn:get_atts(V, [dist(Id,_)]),
get_dist_domain_size(Id, Sz),