Java

I am working in PSO for feature selection. I use KNN algorithm with 10 cross validation for the evaluation. before I use the 10cv the algorithm is quite cheap meaning no high computational cost has been faced, but after turning to 10cv the code is running too slow, sometimes for days. may I know if there is any problem in performing the 10cv. I use the following code to perform 10 cv:

dataset data = FileHandler.loadDataset(new File(dataSetFileName+".csv"), noFeatures, ","); 
                //crossvalidationmat
                  int[][] crossvalidationmat= { 
                    {1,2,3,4,5,6,7,8,9}, 
                    {0,2,3,4,5,6,7,8,9}, 
                    {0,1,3,4,5,6,7,8,9},
                    {0,1,2,4,5,6,7,8,9}, 
                    {0,1,2,3,5,6,7,8,9},
                    {0,1,2,3,4,6,7,8,9},
                    {0,1,2,3,4,5,7,8,9},
                    {0,1,2,3,4,5,6,8,9},
                    {0,1,2,3,4,5,6,7,9},
                    {0,1,2,3,4,5,6,7,8},
                    };
        Dataset[] folds = data.folds((10), new Random(1));
        Dataset training = new DefaultDataset();    //training, testing
        Dataset testing = new DefaultDataset();   
        int[] tr =new int[9];
        int[] te = new int[1]; 
for (int di = 0; di < crossvalidationmat.length; di++) { // start crossvalidation
       System.out.println(crossvalidationmat[di].length);
for (int xj = 0; xj < crossvalidationmat[di].length; xj++) { 
         tr[xj]=crossvalidationmat[di][xj];
         System.out.print(tr[xj]);
    }
    te[0]=di;
    System.out.println("\nTraing  te[0]=di here:  "+te[0]);
        for (int i = 0; i < tr.length; i++) {
            training.addAll(folds[tr[i]]);
        }
        for (int i = 0; i < te.length; i++) {
            testing.addAll(folds[te[i]]);
        }
 Dataset[] foldsTrain = training.folds(numFolds, new Random(1));
//other code
}

class Node {
    char c;
    HashMap<Character, Node> children = new HashMap<Character, Node>();
    boolean isCompleteWord;

    public Node(char c) {
        this.c = c;
        isCompleteWord = false;
    }
    public Node() {
    }
}

List<String> collectWords(char c) {
    List<String> words = new ArrayList<>();
    String word = Character.toString(c);
    Node node = root.children.get(c);
    collectWordsHelper(words, node, word);
    return words;
}

void collectWordsHelper(List<String> words, Node node, String word) {
    for (char i = 'a'; i <= 'z'; i++) {
        if (node.children.containsKey(i)) {
            System.out.println(i); // prints the right letters
            Node child = node.children.get(i);
            word += i;
            if (child.isCompleteWord && !words.contains(word)) {
                words.add(word);
                collectWordsHelper(words, child, "");
            }
            collectWordsHelper(words, child, word);
        }
    }
}

Hello, How to solve this in Java? Generate random simple directed acyclic graph that user inserts the vertex number that each vertex has no less than K-min and not more than K-max neighbours of each vertex. In addition create function in program for given graph insertion and generated graph presentation by user(to print the graph). Generated graph is stored in adjacency list using one-dimensional array. In addtion, according to breadth-first search algortihtm find which vertex is farthest(longest path) from the given vertex and find the path distance. Print the found path between vertices.  If there are some vertices, it is enough one.