start with commenting on distanceClassification.java

Author: max-acc

src/classification/DistanceClassification.java

@@ -25,73 +25,93 @@ public class DistanceClassification {
     private int[][] sortedProbability;
 
 
+    // --- Creating an object for distance classification --------------------------------------------------------------
     protected DistanceClassification(float [][] trainingDataPredictors, String [] trainingDataResults, int rowCount, int columnCount, float density) {
+        //Setting specific attributes
         this.trainingDataPredictors = trainingDataPredictors;
         this.trainingDataResults = trainingDataResults;
         this.rowCount = rowCount;
         this.columnCount = columnCount;
         this.density = density;
 
+        // Getting the different classification classes
         getClassificationClasses();
 
+        // Sorting the classification data
         sortClassificationData();
 
+        // Calculating the mean per feature (to calculate the distance)
         calcFeatureMean();
     }
 
+    // --- Functions for returning classification data for internal use in other classes -------------------------------
+    // --- Function for returning the number of different classes
     protected int getNumberOfClasses () {
         return this.numberOfClasses;
     }
 
+    // --- Function for returning the sorted classification data (after classification)
     protected float[][][] getSortedClassificationData() {
         return this.sortedClassificationData;
     }
 
+    // --- Function for returning the predicted test data (probability per class)
     protected String[][][] getPredictedTestData() {
         return this.predictedTestData;
     }
 
+    // --- Function for returning the sorted probability (ranking of the highest probability)
     protected int[][] getSortedProbability() {
         return this.sortedProbability;
     }
 
+    // --- Function for returning the mean value per feature
     protected float[][] getFeatureMean() {
         return this.featureMean;
     }
 
+    // --- Required Functions for classifying the data -----------------------------------------------------------------
+    // All Functions have to been called in the ClassificationOfFloatValues.java file
+
+    // --- Function for setting the test data (with an upper and lower boundary -> already set in the classification file)
     protected void setTestData(float[][] testDataPredictors, String[] testDataResults, int rowCount, int columnCount) {
         this.testDataPredictors = testDataPredictors;
         this.testDataResults = testDataResults;
         this.testDataRowCount = rowCount;
         this.testDataColumnCount = columnCount;
     }
 
+    // --- Calling a Function for testing the model
     protected void testModel() {
         testClassificationModel();
     }
 
+    // --- Private Functions for intern calculations of the actual classification --------------------------------------
+    // --- Function for getting the different classification classes and their number
     private void getClassificationClasses() {
         int numberOfClasses = 0;
         List<String> classes = new ArrayList<String>();
         List<String> tempClasses = Arrays.asList(this.trainingDataResults);
 
+        // Going through every column of the dataset (test data) and reading the result data (class)
         for (int i = 0; i < this.columnCount; i++) {
+            // If the class is not already in the saved in the class array list, it will be added
             if (!classes.contains(tempClasses.get(i))) {
                 classes.add(tempClasses.get(i));
                 numberOfClasses++;
-                //System.out.println(i);
             }
         }
 
         this.numberOfClasses = numberOfClasses;
         this.classes  = new String[this.numberOfClasses];
 
+        // Converting the array list to an array
         for (int i = 0; i < this.numberOfClasses; i++) {
             this.classes[i] = classes.get(i);
-            //System.out.println(this.classes[i]);
         }
     }
 
+    // --- Function for sorting the classified data
     private void sortClassificationData() {
         ArrayList<ArrayList<ArrayList<Float>>> tempSortedClassificationData = new ArrayList<>();
         int [] tempNumberDataPerClass = new int[this.rowCount -1];
@@ -140,6 +160,7 @@ private void sortClassificationData() {
         }
     }
 
+    // --- Function for calculating the mean for every feature (training the model)
     private void calcFeatureMean() {
         this.featureMean = new float[this.numberOfClasses][this.rowCount -1];
         for (int i = 0; i < this.numberOfClasses; i++) {
@@ -154,6 +175,7 @@ private void calcFeatureMean() {
         }
     }
 
+    // --- Function for testing the classification model
     private void testClassificationModel() {
         this.predictedTestData = new String[this.testDataColumnCount][this.numberOfClasses][2];
         this.sortedProbability = new int[this.testDataColumnCount][this.numberOfClasses];