@@ -11,6 +11,7 @@ public class DATA_evaluation {
1111
1212 private boolean createConfusionMatrix = false ;
1313
14+ // --- Creating a constructor for data evaluation
1415 protected DATA_evaluation (String [] testDataResults , int columnCount , String [][][] predictedTestData , int [][] sortedProbability , int numberOfClasses ) {
1516 this .testDataResults = testDataResults ;
1617 this .columnCount = columnCount ;
@@ -23,20 +24,23 @@ protected DATA_evaluation(String[] testDataResults, int columnCount, String[][][
2324
2425 // --- Function for creating a basic confusion matrix for further calculations -------------------------------------
2526 private void confusionMatrix () {
26- 2727 // Resetting the confusion matrix
2828 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
2929 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
3030 this .confustionMatrix [i ][j ] = 0 ;
3131 }
3232 }
3333
34+ // Going through every column of the data (only test data)
3435 for (int i = 0 ; i < this .columnCount ; i ++) {
36+ // Compare the predicted result with the actual result
3537 if (this .testDataResults [i ].equals (this .predictedTestData [i ][this .sortedProbability [i ][0 ]][0 ])) {
38+ // If true: The data has been predicted truly
3639 this .confustionMatrix [this .sortedProbability [i ][0 ]][this .sortedProbability [i ][0 ]]++;
3740 }
41+ // If the predicted data does not match the actual result, it has been predicted falsely
3842 else {
39- 43+ // Writing data as a false prediction to the confusion matrix
4044 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
4145 if (this .testDataResults [i ].equals (this .predictedTestData [i ][this .sortedProbability [i ][j ]][0 ])) {
4246 this .confustionMatrix [this .sortedProbability [i ][0 ]][this .sortedProbability [i ][j ]]++;
@@ -48,10 +52,12 @@ private void confusionMatrix() {
4852
4953 // --- Printing a basic confusion matrix
5054 protected void getConfusionMatrix () {
55+ // If the confusion matrix has not been created yet, it will be
5156 if (!this .createConfusionMatrix ) {
5257 confusionMatrix ();
5358 }
5459
60+ // Printing every element of the confusion matrix
5561 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
5662 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
5763 System .out .print (confustionMatrix [i ][j ] + " " );
@@ -62,26 +68,32 @@ protected void getConfusionMatrix() {
6268
6369 // --- Printing a simple confusion matrix
6470 protected void getConfusionMatrixSimple () {
71+ // If the confusion matrix has not been created yet, it will be
6572 if (!this .createConfusionMatrix ) {
6673 confusionMatrix ();
6774 }
6875
76+ // Creating an array for calculating a simple confusion matrix
6977 int [][] confusionMatrixSimple = new int [this .numberOfClasses ][2 ];
7078 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
7179 for (int j = 0 ; j < 2 ; j ++) {
7280 confusionMatrixSimple [i ][j ] = 0 ;
7381 }
7482 }
7583
84+ // Going through every column of the data (only test data)
7685 for (int i = 0 ; i < this .columnCount ; i ++) {
86+ // If the data has been predicted correctly it is TT
7787 if (this .testDataResults [i ].equals (this .predictedTestData [i ][this .sortedProbability [i ][0 ]][0 ])) {
7888 confusionMatrixSimple [this .sortedProbability [i ][0 ]][0 ]++;
7989 }
90+ // If the data has been predicted correctly it is TN
8091 else {
8192 confusionMatrixSimple [this .sortedProbability [i ][0 ]][1 ]++;
8293 }
8394 }
8495
96+ // Printing every element of the simple confusion matrix
8597 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
8698 for (int j = 0 ; j < 2 ; j ++) {
8799 System .out .print (confusionMatrixSimple [i ][j ] + " " );
@@ -94,12 +106,17 @@ protected void getConfusionMatrixSimple() {
94106
95107 // --- Printing a normalized confusion matrix
96108 protected void getConfusionMatrixNormalized () {
109+ // If the confusion matrix has not been created yet, it will be
97110 if (!this .createConfusionMatrix ) {
98111 confusionMatrix ();
99112 }
113+ 114+ // Creating an array for calculating a normalized confusion matrix
100115 float [][] confusionMatrixNormalized = new float [this .numberOfClasses ][this .numberOfClasses ];
101116
117+ // Going through every column of the data (only test data)
102118 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
119+ // Adding all predicted values per class
103120 int tempCount = 0 ;
104121 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
105122 tempCount += this .confustionMatrix [i ][j ];
@@ -108,12 +125,14 @@ protected void getConfusionMatrixNormalized() {
108125 if (tempCount == 0 ) {
109126 continue ;
110127 }
128+ 129+ // Dividing the predicted data per class
111130 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
112131 confusionMatrixNormalized [i ][j ] = (float )this .confustionMatrix [i ][j ] / (float )tempCount ;
113132 }
114- 115133 }
116134
135+ // Printing every element of the normalized confusion matrix
117136 for (int i = 0 ; i < this .numberOfClasses ; i ++) {
118137 for (int j = 0 ; j < this .numberOfClasses ; j ++) {
119138 System .out .print (confusionMatrixNormalized [i ][j ] + " " );
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