java.lang.NullPointerException在尝试MOA流聚类算法denstream.WithDBSCAN时(如何正确使用？)

Question

我刚开始使用moa，我很难解释如何使用聚类算法。文档缺乏用于常见用法的示例代码，实现没有得到很好的注释.也没有找到任何教程。

下面是我的代码：

import com.yahoo.labs.samoa.instances.DenseInstance;
import moa.cluster.Clustering;
import moa.clusterers.denstream.WithDBSCAN;

public class TestingDenstream {
    static DenseInstance randomInstance(int size) {
        DenseInstance instance = new DenseInstance(size);
        for (int idx = 0; idx < size; idx++) {
            instance.setValue(idx, Math.random());
        }
        return instance;
    }
    public static void main(String[] args) {
        WithDBSCAN withDBSCAN = new WithDBSCAN();
        withDBSCAN.resetLearningImpl();
        for (int i = 0; i < 10; i++) {
            DenseInstance d = randomInstance(2);
            withDBSCAN.trainOnInstanceImpl(d);
        }
        Clustering clusteringResult = withDBSCAN.getClusteringResult();
        Clustering microClusteringResult = withDBSCAN.getMicroClusteringResult();

        System.out.println(clusteringResult);

    }
}

这是我所犯的错误：

​

​

对于如何使用该算法的任何见解都将受到赞赏。谢谢!

Answer 1

我已经更新了密码。正如我在github中提到的那样，它正在工作，您必须将头分配给实例。见github讨论

以下是更新的代码：

    static DenseInstance randomInstance(int size) {
        // generates the name of the features which is called as InstanceHeader
        ArrayList<Attribute> attributes = new ArrayList<Attribute>();
        for (int i = 0; i < size; i++) {
            attributes.add(new Attribute("feature_" + i));
        }
        // create instance header with generated feature name
        InstancesHeader streamHeader = new InstancesHeader(
                new Instances("Mustafa Çelik Instance",attributes, size));

        // generates random data
        double[] data = new double[2];
        Random random = new Random();
        for (int i = 0; i < 2; i++) {
            data[i] = random.nextDouble();
        }

        // creates an instance and assigns the data
        DenseInstance inst = new DenseInstance(1.0, data);

        // assigns the instanceHeader(feature name)
        inst.setDataset(streamHeader);

        return inst;
    }

    public static void main(String[] args) {
        WithDBSCAN withDBSCAN = new WithDBSCAN();
        withDBSCAN.resetLearningImpl();
        withDBSCAN.initialDBScan();
        for (int i = 0; i < 1500; i++) {
            DenseInstance d = randomInstance(5);

            withDBSCAN.trainOnInstanceImpl(d);
        }
        Clustering clusteringResult = withDBSCAN.getClusteringResult();
        Clustering microClusteringResult = withDBSCAN.getMicroClusteringResult();

        System.out.println(clusteringResult);
    }

下面是调试过程的屏幕截图，您可以看到生成了集群结果：

​

图像链接被破坏，您可以在github github入口链接上找到它