小编Abe*_*oor的帖子

如何hashmap按整数值排序a ,我找到的答案之一就在这里

由Evgeniy Dorofeev撰写,他的回答是这样的

HashMap<String, Integer> map = new HashMap<String, Integer>();
    map.put("a", 4);
    map.put("c", 6);
    map.put("b", 2);
    Object[] a = map.entrySet().toArray();
    Arrays.sort(a, new Comparator() {
        public int compare(Object o1, Object o2) {
            return ((Map.Entry<String, Integer>) o2).getValue().compareTo(
                    ((Map.Entry<String, Integer>) o1).getValue());
        }
    });
    for (Object e : a) {
        System.out.println(((Map.Entry<String, Integer>) e).getKey() + " : "
                + ((Map.Entry<String, Integer>) e).getValue());
    }

产量

c : 6
a : 4
b : 2

我的问题是如何成为描述？如果我想对HashMap Asc进行排序我该怎么做？ …

我正在使用ELKI我KMeansLloyd<NumberVector> with k=3 每次运行我的java代码时使用的数据集群我得到完全不同的集群结果,这是正常的还是我应该做些什么来使我的输出几乎稳定？这里是我从elki教程获得的代码

DatabaseConnection dbc = new ArrayAdapterDatabaseConnection(a);
    // Create a database (which may contain multiple relations!)
    Database db = new StaticArrayDatabase(dbc, null);
    // Load the data into the database (do NOT forget to initialize...)
    db.initialize();
    // Relation containing the number vectors:
    Relation<NumberVector> rel = db.getRelation(TypeUtil.NUMBER_VECTOR_FIELD);
    // We know that the ids must be a continuous range:
    DBIDRange ids = (DBIDRange) rel.getDBIDs();

    // K-means should be used with squared Euclidean (least squares):
    //SquaredEuclideanDistanceFunction dist = SquaredEuclideanDistanceFunction.STATIC; …