Changeset 38 for trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing

Timestamp:

06/11/15 11:27:33 (10 years ago)

Author:

sherbold

Message:

• added Oversampling and Resampling processors
• fixed bug in ZScoreNormalizations
• added new load for the Audi data set that is based on changes
• minor changes to remove warnings

Location:

trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing

Files:

• Oversampling.java (added)
• Resampling.java (added)
• ZScoreNormalization.java (modified) (2 diffs)
• ZScoreTargetNormalization.java (modified) (2 diffs)

trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/ZScoreNormalization.java

@@ -44 +44 @@
         
         private void normalize(Instances instances) {
+                instances.toString();
                 final Attribute classAttribute = instances.classAttribute();
                 
@@ -56 +57 @@
                         }
                 }
-                
                 for( int i=0 ; i<instances.numAttributes(); i++) {
                         if( !instances.attribute(i).equals(classAttribute) ) {
-                                for( int j=0 ; j<instances.numAttributes() ; j++ ) {
+                                for( int j=0 ; j<instances.numInstances() ; j++ ) {
                                         Instance inst = instances.get(i);
-                                        double newValue = (inst.value(j)-means[j])/stddevs[j];
-                                        inst.setValue(j, newValue);
+                                        double newValue = (inst.value(i)-means[i])/stddevs[i];
+                                        if( newValue==Double.NaN ) {
+                                                System.out.println("foooooo");
+                                        }
+                                        inst.setValue(i, newValue);
                                 }
                         }

trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/ZScoreTargetNormalization.java

@@ -44 +44 @@
                 for( int i=0 ; i<testdata.numInstances() ; i++ ) {
                         Instance instance = testdata.instance(i);
-                        for( int j=0 ; j<testdata.numInstances() ; j++ ) {
+                        for( int j=0 ; j<testdata.numAttributes() ; j++ ) {
                                 if( testdata.attribute(j)!=classAttribute ) {
                                         instance.setValue(j, instance.value(j)-meanTest[j]/stddevTest[j]);
@@ -85 +85 @@
                 for( int i=0 ; i<testdata.numInstances() ; i++ ) {
                         Instance instance = testdata.instance(i);
-                        for( int j=0 ; j<testdata.numInstances() ; j++ ) {
+                        for( int j=0 ; j<testdata.numAttributes() ; j++ ) {
                                 if( testdata.attribute(j)!=classAttribute ) {
                                         instance.setValue(j, instance.value(j)-meanTest[j]/stddevTest[j]);