WIP: Resolve "coherence des arbres de predictions"

Closes #20 (closed)

code/bolsonaro/trainer.py

@@ -145,16 +145,14 @@ class Trainer(object):
         from sklearn.preprocessing import normalize
         import itertools
 
-        if type(model) in [OmpForestRegressor, SimilarityForestRegressor, KMeansForestRegressor, EnsembleSelectionForestRegressor]:
-            estimators = model.forest
-        elif type(model) in [OmpForestBinaryClassifier, OmpForestMulticlassClassifier]:
+        if type(model) in [OmpForestRegressor, SimilarityForestRegressor, KMeansForestRegressor, EnsembleSelectionForestRegressor,
+            OmpForestBinaryClassifier, OmpForestMulticlassClassifier]:
             estimators = model.forest
+            estimators = np.asarray(estimators)[model._omp.coef_ != 0]
         elif type(model) in [RandomForestRegressor, RandomForestClassifier]:
             estimators = model.estimators_
 
-        predictions = list()
-        for ti in estimators:
-            predictions.append(ti.predict(X))
+        predictions = np.array([tree.predict(X) for tree in estimators])
 
         predictions = normalize(predictions)