Switch to ANN for classification

Brainy uses ANNs, so we should too. Note: Random Forest yield better
results.

train_model.py

@@ -602,11 +602,12 @@ if __name__ == "__main__":
 
     classifier_creators = {"RandomForest" : lambda : RandomForestClassifier(),
                            "LDA": lambda : LinearDiscriminantAnalysis(n_components=2),
-                           "ANN" : lambda : MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(5, 5),
+                           "ANN" : lambda : MLPClassifier(solver='lbfgs', alpha=1e-5, max_iter=1000,
+                                                          hidden_layer_sizes=(5, 5),
                                                           random_state=1) }
 
     classifiers = train_classifiers(training_data["data"],
-                                    classifier_creators["RandomForest"],
+                                    classifier_creators["ANN"],
                                     "Best datastructure",
                                     training_data["software_selected_columns"] + training_data["hardware_selected_columns"],
                                     "Param: datastructureName")