add preference

eraser.starter/starter-setting.yaml

@@ -37,10 +37,11 @@ activity:
 
 # Model for preference learning. If dummy is true, then the file parameter is ignored.
 preference:
-  factory: de.tudresden.inf.st.eraser.starter.TestMachineLearningHandlerFactory
+  factory: de.tudresden.inf.st.eraser.feedbackloop.learner_backup.MachineLearningHandlerFactoryImpl
+ # factory: de.tudresden.inf.st.eraser.starter.TestMachineLearningHandlerFactory
   # File to read in. Expected format depends on factory
-  file: src/main/resources/testHandler.properties
-#  file: ../datasets/backup/preference_data.csv
+#  file: src/main/resources/testHandler.properties
+  file: ../datasets/backup/preference_data.csv
   external: true
   # Use dummy model in which the current activity is directly editable. Default: false.
   dummy: false

feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java

@@ -104,7 +104,6 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
              or let knowledge base pass all relevant items <- push model
     */
     if (this.goal == GOAL_ACTIVITY_PHONE_AND_WATCH) {
-
       for (Item item : changedItems) {
         if(item.getID().equals("m_accel_x"))
         {
@@ -125,7 +124,7 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
             empty = true;
           }
         }
-        if(!empty){
+        if(!empty){logger.info("debug_activity_new_data");
           this.activity_result = learner.activity_predictor(a_new_data);
         }
         a_length = 0;