eclipse My Weka Java代码结果*Weka*虚拟*STRING*用于*STRING*属性*

Question

我有一个通过WEKA GUI生成的J48模型，并计划在我的WEKA JAVA代码中使用它。我想用这个模型来实时预测我的数据。我的代码如下：

public static void dt(String type, String bitrate, String resolution, String fps, String duration){
    String rootPath="/home/weka/Documents/";

    Attribute attr1 = new Attribute("type", (FastVector) null);
    Attribute attr2 = new Attribute("bitrate", (FastVector) null);
    Attribute attr3 = new Attribute("resolution", (FastVector) null);
    Attribute attr4 = new Attribute("fps", (FastVector) null);
    Attribute attr5 = new Attribute("duration", (FastVector) null);
    Attribute attr6 = new Attribute("class", (FastVector) null);

    FastVector attributes = new FastVector();

    attributes.addElement(attr1);
    attributes.addElement(attr2);
    attributes.addElement(attr3);
    attributes.addElement(attr4);
    attributes.addElement(attr5);
    attributes.addElement(attr6);

    Instances testing = new Instances("Test-dataset", attributes, 0);
    testing.setClassIndex(testing.numAttributes() - 1);

    double[] values = new double[testing.numAttributes()];

    values[0] = testing.attribute(0).addStringValue(type);
    values[1] = testing.attribute(1).addStringValue(bitrate);
    values[2] = testing.attribute(2).addStringValue(resolution);
    values[3] = testing.attribute(3).addStringValue(fps);
    values[4] = testing.attribute(4).addStringValue(duration);

    Instance inst = new Instance(1.0, values);

    inst.setValue(testing.attribute(0), values[0]);
    inst.setValue(testing.attribute(1), values[1]);
    inst.setValue(testing.attribute(2), values[2]);
    inst.setValue(testing.attribute(3), values[3]);
    inst.setValue(testing.attribute(4), values[4]);

    System.out.println("The instance: "+inst);

    testing.add(inst);

    try {
        Classifier cls = (Classifier) weka.core.SerializationHelper.read(rootPath+"multimedia.model");
        double myValue = cls.classifyInstance(testing.lastInstance());
        String prediction = testing.classAttribute().value((int) myValue);

        System.out.println("The predicted value of the data = "+prediction);
    } catch (Exception e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }
}

我的代码的结果是：

==Service parameter information==
Service ID : 1
Type : audio
Bitrate : 96
Resolution : 0
FPS : 0
Duration : 20
The instance: 1,1,1,1,1,0
The predicted value of the data = *WEKA*DUMMY*STRING*FOR*STRING*ATTRIBUTES*

我的值似乎没有包含在实例和生成的Weka伪消息中。我的代码哪里出错了？我已经搜索了教程并用谷歌搜索了答案，但我找不到答案

谢谢

Answer 1

谢谢你的评论，幽灵猫。我得到了朋友的帮助来解决这个问题。更新代码如下：

public static void dt(String type, String bitrate, String resolution, String fps, String duration){
    String rootPath="/home/weka/Documents/";

    Attribute attr1 = new Attribute("type", (FastVector) null);
    //Attribute attr2 = new Attribute("bitrate", (FastVector) null);
    Attribute attr2 = new Attribute("bitrate");
    Attribute attr3 = new Attribute("resolution", (FastVector) null);
    //Attribute attr4 = new Attribute("fps", (FastVector) null);
    Attribute attr4 = new Attribute("fps");
    //Attribute attr5 = new Attribute("duration", (FastVector) null);
    Attribute attr5 = new Attribute("duration");
    Attribute attr6 = new Attribute("class", (FastVector) null);

    FastVector attributes = new FastVector();

    attributes.addElement(attr1);
    attributes.addElement(attr2);
    attributes.addElement(attr3);
    attributes.addElement(attr4);
    attributes.addElement(attr5);
    attributes.addElement(attr6);


    Instances testing = new Instances("multimedia", attributes, 0);
    testing.setClassIndex(testing.numAttributes() - 1);

    double[] values = new double[testing.numAttributes()];
    values[0] = testing.attribute(0).addStringValue(type);
    values[1] = Integer.parseInt(bitrate);
    values[2] = testing.attribute(2).addStringValue(resolution);
    values[3] = Integer.parseInt(fps);
    values[4] = Integer.parseInt(duration);

    Instance test = new Instance(1, values);
    testing.add(test);

    System.out.println("The instance: "+testing);

    try {
        Classifier cls = (Classifier) weka.core.SerializationHelper.read(rootPath+"multimedia.model");
        //double myValue = cls.classifyInstance(testing.lastInstance());
        //double myValue = cls.classifyInstance(testing.firstInstance());
        //String prediction = testing.classAttribute().value((int) myValue);
        System.out.println(cls.classifyInstance(testing.firstInstance()));
        //String prediction = testing.classAttribute().value((int) myValue);

        //System.out.println("The predicted value of the data = "+prediction);
    } catch (Exception e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }
}

结果如下：

    Received JSON : {"id":"1","duration":"30","flag":"start","fps":"24","bitrate":"128","resolution":"720p","type":"video"}

==Service parameter information==
Service ID : 1
Type : video
Bitrate : 128
Resolution : 720p
FPS : 24
Duration : 30
The instance: @relation multimedia

@attribute type string
@attribute bitrate numeric
@attribute resolution string
@attribute fps numeric
@attribute duration numeric
@attribute class string

@data
video,128,720p,24,30,*WEKA*DUMMY*STRING*FOR*STRING*ATTRIBUTES*
0.0

似乎我们已经基于新数据创建了实例。然而，它不能按模型进行分类，并导致STRING属性的WEKADUMMYSTRING。你或任何人能帮我吗，为什么会有这样的结果？谢谢你