add evaluation of results

Author: max-acc

src/Main.java

@@ -21,6 +21,8 @@ public static void main (String[] args) throws Exception {
         ob.dataSubdivision();
         //System.out.println(ob.feedback()[0][2]);
         ob.distanceClassification();
+
+        ob.evaluateResults();
     }
 
 }

src/classification/ClassificationOfFloatValues.java

@@ -27,6 +27,10 @@ public class ClassificationOfFloatValues {
     private boolean dataSubdivisionBool = false; // Data has been divided into training and test data
     private String MLAlgorithm;     // Variable for saving which machine learning algorithm has been used
 
+    // --- Classification result data variables
+    private String[][][] predictedTestData;
+    private int[][] sortedProbability;
+
 
     // Function to add the members of the class
     public float[][] output() { return this.predictorData; }
@@ -83,6 +87,12 @@ public void dataValidation (float trainingData) {
 
 
     // --- Functions for evaluating the machine learning results -------------------------------------------------------
+    public void evaluateResults() {
+        DATA_evaluation evaluationObject    = new DATA_evaluation(this.testDataResults,
+                this.columnCount - this.numberOfTrainingData,
+                this.predictedTestData,
+                this.sortedProbability);
+    }
     public void confusionMatrix() {
         if (this.MLAlgorithm == "DistanceClassification") {
             System.out.println("nice confusion");
@@ -134,6 +144,10 @@ public void distanceClassification (){
             // Testing the distance classification model
             classificationObject.setTestData(this.testDataPredictors, this.testDataResults, this.rowCount, this.columnCount - this.numberOfTrainingData);
             classificationObject.testModel();
+
+            // Get the test data
+            this.predictedTestData  = classificationObject.getPredictedTestData();
+            this.sortedProbability  = classificationObject.getSortedProbability();
         }
 
     }

src/classification/DATA_evaluation.java

@@ -0,0 +1,16 @@
+package classification;
+
+public class DATA_evaluation {
+    private String[][][] predictedTestData;
+    private int[][] sortedProbability;
+
+    private int columnCount;
+    private String [] testDataResults;
+
+    protected DATA_evaluation(String[] testDataResults, int columnCount, String[][][] predictedTestData, int[][] sortedProbability) {
+        this.testDataResults    = testDataResults;
+        this.columnCount        = columnCount;
+        this.predictedTestData  = predictedTestData;
+        this.sortedProbability  = sortedProbability;
+    }
+}

src/classification/DistanceClassification.java

@@ -43,6 +43,14 @@ protected float[][][] getSortedClassificationData() {
         return this.sortedClassificationData;
     }
 
+    protected String[][][] getPredictedTestData() {
+        return this.predictedTestData;
+    }
+
+    protected int[][] getSortedProbability() {
+        return this.sortedProbability;
+    }
+
     protected float[][] getFeatureMean() {
         return this.featureMean;
     }
@@ -204,17 +212,6 @@ private void testClassificationModel() {
                 }
                 this.sortedProbability[i][j] = tempIndex;
             }
-
-
-
-            System.out.println(this.sortedProbability[i][0]);
-            System.out.println(this.sortedProbability[i][1]);
-            System.out.println(this.sortedProbability[i][2]);
-
-
-            if (i == 5) {
-                break;
-            }
         }
     }
 }