Solve checkstyle issues

src/main/java/be/cylab/java/wowa/training/MainTest.java

@@ -65,13 +65,15 @@ public final class MainTest {
         System.out.println("Wowa training");
         HashMap<AbstractSolution, Double> map_wt = trainer.runKFold(folds, 10);
         long end_time = System.currentTimeMillis();
-        System.out.println("Execution time : " + (end_time - start_time) / 1000 + " seconds");
+        System.out.println("Execution time : " + (end_time - start_time) / 1000
+                + " seconds");
 
         start_time = System.currentTimeMillis();
         System.out.println("Neural Network learning");
         HashMap<MultiLayerNetwork, Double> map_nn = nn.runKFold(folds, 10);
         end_time = System.currentTimeMillis();
-        System.out.println("Execution time : " + (end_time - start_time) / 1000 + " seconds");
+        System.out.println("Execution time : " + (end_time - start_time) / 1000
+                + " seconds");
 
         double nn_score = 0.0;
         double wt_score = 0.0;

src/main/java/be/cylab/java/wowa/training/NeuralNetwork.java

@@ -138,7 +138,7 @@ public final class NeuralNetwork {
                     record_reader, 12468, FEATURES_COUNT, CLASSES_COUNT);
             DataSet all_data = iterator.next();
             //DataSet training_data
-            //        = prepareDataSetForTrainingAndTesting(all_data).getTrain();
+            //       = prepareDataSetForTrainingAndTesting(all_data).getTrain();
             return learning(all_data);
 
         } catch (IOException e) {

src/main/java/be/cylab/java/wowa/training/Trainer.java

@@ -162,7 +162,7 @@ public class Trainer {
      * @param increase_ratio
      * @return
      */
-    HashMap<AbstractSolution, Double> runKFold(
+    final HashMap<AbstractSolution, Double> runKFold(
             final List<TrainingDataset> prepared_folds,
             final int increase_ratio) {
         HashMap<AbstractSolution, Double> map = new HashMap<>();