Changeset 20 for trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalTraining2.java

Timestamp:

10/31/14 15:54:08 (10 years ago)

Author:

atrautsch

Message:

Mehr kommentiert.

File:

• trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalTraining2.java (modified) (5 diffs)

trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalTraining2.java

@@ -84 +84 @@
                 private HashMap<Integer, ArrayList<Double[][]>> csize;
                 
+                /* debug vars */
+                @SuppressWarnings("unused")
                 private boolean show_biggest = true;
                 
+                @SuppressWarnings("unused")
                 private int CFOUND = 0;
+                @SuppressWarnings("unused")
                 private int CNOTFOUND = 0;
                 
@@ -260 +264 @@
                                 //}
 
-                                // now it can happen that we dont find a cluster because we deleted it previously (too few instances)
+                                // now it can happen that we do not find a cluster because we deleted it previously (too few instances)
                                 // or we get bigger distance measures from weka so that we are completely outside of our clusters.
                                 // in these cases we just find the nearest cluster to our instance and use it for classification.
@@ -280 +284 @@
                                 }
                                 
-                                // here we have the cluster where an instance has the minimum distance between itself the
+                                // here we have the cluster where an instance has the minimum distance between itself and the
                                 // instance we want to classify
                                 // if we still have not found a cluster we exit because something is really wrong
@@ -436 +440 @@
                         */
                         
-                    // train one classifier per cluster, we get the clusternumber from the traindata
+                    // train one classifier per cluster, we get the cluster number from the traindata
                     int cnumber;
                         Iterator<Integer> clusternumber = ctraindata.keySet().iterator();
@@ -444 +448 @@
                         while ( clusternumber.hasNext() ) {
                                 cnumber = clusternumber.next();
-                                cclassifier.put(cnumber,setupClassifier()); // das hier ist der eigentliche trainer 
+                                cclassifier.put(cnumber,setupClassifier());  // this is the classifier used for the cluster 
                                 cclassifier.get(cnumber).buildClassifier(ctraindata.get(cnumber));
                                 //Console.traceln(Level.INFO, String.format("classifier in cluster "+cnumber));