Updating adaboost

src/methods/adaboost/adaboost.cpp

@@ -78,11 +78,6 @@ void initModelWithTraining(float *dataMatArr, SP_integer dataMatSize, SP_integer
 void initModelNoTraining(double tol = 1e-6, 
 							char const *learner = "perceptron")
 {
-	if(tol <= 0)
-	{
-		raisePrologDomainExeption(tol, 1, ">0", "initModelNoTraining");
-	}
-
 	if(strcmp(learner, "perceptron") == 0) 
 	{
 		usingPerceptron = true;
@@ -215,11 +210,6 @@ double getTolerance()
 //
 void modifyTolerance(double newTol)
 {
-
-	if(newTol <= 0)
-	{
-		raisePrologDomainExeption(newTol, 1, ">0", "modifyTolerance");
-	}
 	if(usingPerceptron) 
 	{
 		double& tol = adaBoostPerceptron.Tolerance();

src/methods/adaboost/adaboost.pl

@@ -38,23 +38,25 @@
 %%
 %%            Initiates the Adaboostmodel and trains it, so classify can be used immediately.
 %%
-foreign(initModelWithTraining, c, initModelWithTraining(+pointer(float_array), +integer, +integer, 
-                                                        +pointer(float_array), +integer, 
-                                                        +integer, 
-                                                        +string, 
-                                                        +integer , +float32)).
-
 initModelWithTraining(MatList, MatRows, VecList, NumClasses, Learner, Iterations, Tolerance) :-
         NumClasses >= 0,
         Iterations >= 0,
-        Tolerance >= 0,
+        Tolerance > 0,
         convert_list_to_float_array(MatList, MatRows, array(Xsize, Xrownum, X)),
         convert_list_to_float_array(VecList, array(Ysize, Y)),
-        initModelWithTraining(X, Xsize, Xrownum, Y, Ysize, NumClasses, Learner, Iterations, Tolerance).
+        initModelWithTrainingI(X, Xsize, Xrownum, Y, Ysize, NumClasses, Learner, Iterations, Tolerance).
+
+foreign(initModelWithTraining, c, initModelWithTrainingI(+pointer(float_array), +integer, +integer, 
+                                                        +pointer(float_array), +integer, 
+                                                        +integer, 
+                                                        +string, 
+                                                        +integer , +float32)).
+
+
 
 %% --Input--
-%%            string learner       => "decision_stump", "perceptron",
 %%            float  tolerance     => 1e-6
+%%            string learner       => "decision_stump", "perceptron",
 %%
 %% --Output--
 %%
@@ -62,7 +64,11 @@ initModelWithTraining(MatList, MatRows, VecList, NumClasses, Learner, Iterations
 %%            Needs to be called first before all other predicates exept initModelWithTraining!
 %%            Initiates the Adaboostmodel but doesnt train it, so train has to be used first before classify can be used.
 %%
-foreign(initModelNoTraining, c, initModelNoTraining(+float32, +string)).
+initModelNoTraining(Tolerance, Learner) :-
+        Tolerance > 0,
+        initModelNoTrainingI(Tolerance, Learner).
+
+foreign(initModelNoTraining, c, initModelNoTrainingI(+float32, +string)).
 
 
 %% --Input--
@@ -75,16 +81,18 @@ foreign(initModelNoTraining, c, initModelNoTraining(+float32, +string)).
 %% --Description--
 %%            Classifies the given data into the number of classes the model was trained for.
 %%
-foreign(classify, c, classify(  +pointer(float_array), +integer, +integer, 
-                                -pointer(float_array), -integer, 
-                                -pointer(float_array), -integer, -integer)).
-
 classify(TestList, TestRows, PredicList, ProbsList, ZRows) :-
         convert_list_to_float_array(TestList, TestRows, array(Xsize, Xrownum, X)),
-        classify(X, Xsize, Xrownum, Y, Ysize, Z, ZCols, ZRows),
+        classifyI(X, Xsize, Xrownum, Y, Ysize, Z, ZCols, ZRows),
         convert_float_array_to_list(Y, Ysize, PredicList),
         convert_float_array_to_2d_list(Z, ZCols, ZRows, ProbsList).
 
+foreign(classify, c, classifyI(  +pointer(float_array), +integer, +integer, 
+                                -pointer(float_array), -integer, 
+                                -pointer(float_array), -integer, -integer)).
+
+
+
 
 %% --Input--
 %%
@@ -94,7 +102,10 @@ classify(TestList, TestRows, PredicList, ProbsList, ZRows) :-
 %% --Description--
 %%            Returns the amount of classes defined in the model for classification.
 %%
-foreign(numClasses, c, numClasses([-integer])).
+numClasses(ClassesNum) :-
+        numClassesI(ClassesNum).
+
+foreign(numClasses, c, numClassesI([-integer])).
 
 
 %% --Input--
@@ -105,7 +116,10 @@ foreign(numClasses, c, numClasses([-integer])).
 %% --Description--
 %%            Returns the tolerance of the model.
 %%
-foreign(getTolerance, c, getTolerance([-float32])).
+getTolerance(Tolerance) :-
+        getToleranceI(Tolerance).
+
+foreign(getTolerance, c, getToleranceI([-float32])).
 
 
 %% --Input--
@@ -116,7 +130,11 @@ foreign(getTolerance, c, getTolerance([-float32])).
 %% --Description--
 %%            Modifies the tolerance of the model.
 %%
-foreign(modifyTolerance, c, modifyTolerance(+float32)).
+modifyTolerance(NewTolerance) :-
+        NewTolerance > 0,
+        modifyToleranceI(NewTolerance).
+
+foreign(modifyTolerance, c, modifyToleranceI(+float32)).
 
 
 %% --Input--
@@ -131,20 +149,22 @@ foreign(modifyTolerance, c, modifyTolerance(+float32)).
 %%            float  double upper bound training error
 %%
 %% --Description--
-foreign(train, c, train(    +pointer(float_array), +integer, +integer, 
-                            +pointer(float_array), +integer, 
-                            +integer, 
-                            +string, 
-                            +integer , +float32, 
-                            [-float32])).
-
 train(MatList, MatRows, VecList, NumClasses, Learner, Iterations, Tolerance, Error) :-
         NumClasses >= 0,
         Iterations >= 0,
         Tolerance >= 0,
         convert_list_to_float_array(MatList, MatRows, array(Xsize, Xrownum, X)),
         convert_list_to_float_array(VecList, array(Ysize, Y)),
-        train(X, Xsize, Xrownum, Y, Ysize, NumClasses, Learner, Iterations, Tolerance, Error).
+        trainI(X, Xsize, Xrownum, Y, Ysize, NumClasses, Learner, Iterations, Tolerance, Error).
+
+foreign(train, c, trainI(    +pointer(float_array), +integer, +integer, 
+                            +pointer(float_array), +integer, 
+                            +integer, 
+                            +string, 
+                            +integer , +float32, 
+                            [-float32])).
+
+
 
 
 %% Defines the functions that get connected from main.cpp

src/methods/adaboost/adaboost_test.pl

@@ -62,13 +62,10 @@ test(initModelWithTraining_DecisionStump) :-
 
 %% Failure Tests
 
-test(initModelNoTraining_WrongInputTypes, [error(type_error(number ,wrong), _)]) :-
-        initModelNoTraining(wrong, 1).
-
 test(initModelNoTraining_WrongLearner, [error(domain_error('perceptron or decision_stump' ,wrongLearner), _)]) :-
         initModelNoTraining(0.0001, wrongLearner).
 
-test(initModelNoTraining_WrongTol, [error(domain_error('>0' ,-1.0), _)]) :-
+test(initModelNoTraining_WrongTol, fail) :-
         initModelNoTraining(-1.0, perceptron).
 
 %% Successful Tests
@@ -197,7 +194,7 @@ test(getTolerance_afterTrain, [true(Amount =:= 0.0005)]) :-
 :- begin_tests(modifyTolerance).
 
 %% Failure Tests
-test(modifyTolerance_With_Negative_Input, [error(domain_error('>0' , -0.02), _)]) :-
+test(modifyTolerance_With_Negative_Input, fail) :-
         reset_Model_No_Train(perceptron),
         modifyTolerance(-0.02).
 
@@ -319,3 +316,4 @@ test(train_After_InitTrain_Decision_Stump, [true(Error =:= 1)]) :-
 
 run_adaboost_tests :-
         run_tests.
+