Final cleanup in files

Went trough the files once more time to remove remaining one-line comments Didn't removed the comment from the benchmark on line 107 I think it is useful.
Samyssmile · Oct 11, 2023 · f1e8ce8 · f1e8ce8
1 parent 34daf51
commit f1e8ce8
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Showing 8 changed files with 8 additions and 11 deletions.
diff --git a/example/src/main/java/de/example/benchmark/Benchmark.java b/example/src/main/java/de/example/benchmark/Benchmark.java
@@ -90,7 +90,6 @@ private void run() {
         });
 
 
-        //Sort and print results with numeration begin with best average accuracy
         System.out.println("Classifier performances (sorted by average accuracy):");
         results.entrySet().stream()
                 .map(entry -> {

diff --git a/example/src/main/java/de/example/data/seaborn/SeabornDataProcessor.java b/example/src/main/java/de/example/data/seaborn/SeabornDataProcessor.java
@@ -145,7 +145,7 @@ public double[][] getTestLabels() {
     }
 
     private double[][] featuresOf(List<Penguin> data) {
-        double[][] features = new double[data.size()][4]; // 4 numerische Eigenschaften
+        double[][] features = new double[data.size()][4];
 
         for (int i = 0; i < data.size(); i++) {
             Penguin p = data.get(i);
@@ -159,7 +159,7 @@ private double[][] featuresOf(List<Penguin> data) {
     }
 
     private double[][] labelsOf(List<Penguin> data) {
-        double[][] labels = new double[data.size()][3]; // 3 Pinguinarten
+        double[][] labels = new double[data.size()][3];
 
         for (int i = 0; i < data.size(); i++) {
             Penguin p = data.get(i);

diff --git a/example/src/main/java/de/example/knn/KnnIrisExample.java b/example/src/main/java/de/example/knn/KnnIrisExample.java
@@ -27,7 +27,7 @@ public static void main(String[] args) {
         irisDataProcessor.split(data, TRAIN_TEST_SPLIT_RATIO);
 
         Classifier knn = new KnnClassifier(2);
-        //Train and evaluate
+
         knn.train(irisDataProcessor.getTrainFeatures(), irisDataProcessor.getTrainLabels());
         knn.evaluate(irisDataProcessor.getTestFeatures(), irisDataProcessor.getTestLabels());
     }

diff --git a/example/src/main/java/de/example/knn/KnnSeabornExample.java b/example/src/main/java/de/example/knn/KnnSeabornExample.java
@@ -22,13 +22,13 @@ public class KnnSeabornExample {
     private static final File CSV_FILE = new File("example" + File.separator + "datasets" + File.separator + "seaborn-penguins" + File.separator + "penguins.csv");
 
     public static void main(String[] args) {
-        //Load Data, shuffle, normalize, filter incomplete records out.
         var seabornDataProcessor = new SeabornDataProcessor();
         List<Penguin> data = seabornDataProcessor.loadDataSetFromCSV(CSV_FILE, ',', SHUFFLE, NORMALIZE, FILTER_INCOMPLETE_RECORDS);
-        //Split dataset into train and test
+
         Dataset<Penguin> dataset = seabornDataProcessor.split(data, TRAIN_TEST_SPLIT_RATIO);
         var seabornProvider = new SeabornProvider(data, dataset.trainData(), dataset.testData());
         seabornProvider.printStatistics();
+
         Classifier knn = new KnnClassifier(2);
         knn.train(seabornProvider.getTrainFeatures(), seabornProvider.getTrainLabels());
         knn.evaluate(seabornProvider.getTestFeatures(), seabornProvider.getTestLabels());

diff --git a/lib/src/main/java/de/edux/data/reader/CSVIDataReader.java b/lib/src/main/java/de/edux/data/reader/CSVIDataReader.java
@@ -14,7 +14,7 @@
 public class CSVIDataReader implements IDataReader {
 
     public List<String[]> readFile(File file, char separator) {
-        CSVParser customCSVParser = new CSVParserBuilder().withSeparator(separator).build(); // custom separator
+        CSVParser customCSVParser = new CSVParserBuilder().withSeparator(separator).build();
         List<String[]> result;
         try(CSVReader reader = new CSVReaderBuilder(
                 new FileReader(file))

diff --git a/lib/src/main/java/de/edux/ml/randomforest/RandomForest.java b/lib/src/main/java/de/edux/ml/randomforest/RandomForest.java
@@ -129,7 +129,6 @@ public double[] predict(double[] feature) {
         for (Future<double[]> future : futures) {
             try {
                 double[] prediction = future.get();
-                /*               voteMap.merge(prediction, 1L, Long::sum);*/
                 double label = getIndexOfHighestValue(prediction);
                 voteMap.merge(label, 1L, Long::sum);
             } catch (InterruptedException | ExecutionException e) {

diff --git a/lib/src/test/java/de/edux/data/provider/DataProcessorTest.java b/lib/src/test/java/de/edux/data/provider/DataProcessorTest.java
@@ -105,7 +105,6 @@ private DataProcessor<String> getDummyDataUtil() {
 
             @Override
             public void normalize(List<String> dataset) {
-                // Mock normalize for the sake of testing
             }
 
             @Override

diff --git a/lib/src/test/java/de/edux/data/provider/SeabornDataProcessor.java b/lib/src/test/java/de/edux/data/provider/SeabornDataProcessor.java
@@ -143,7 +143,7 @@ public double[][] getTestLabels() {
     }
 
     private double[][] featuresOf(List<Penguin> data) {
-        double[][] features = new double[data.size()][4]; // 4 numerische Eigenschaften
+        double[][] features = new double[data.size()][4];
 
         for (int i = 0; i < data.size(); i++) {
             Penguin p = data.get(i);
@@ -157,7 +157,7 @@ private double[][] featuresOf(List<Penguin> data) {
     }
 
     private double[][] labelsOf(List<Penguin> data) {
-        double[][] labels = new double[data.size()][3]; // 3 Pinguinarten
+        double[][] labels = new double[data.size()][3];
 
         for (int i = 0; i < data.size(); i++) {
             Penguin p = data.get(i);