WEKA分类可能性

Question

我想知道WEKA是否有办法为分类输出一些"最佳猜测".

我的场景是:例如,我使用交叉验证对数据进行分类,然后在weka的输出上得到类似的结果:这些是对此实例进行分类的3个最佳猜测.我想要的是,即使一个实例没有被正确分类,我得到该实例的3或5个最佳猜测的输出.

例:

课程:A,B,C,D,E实例:1 ... 10

输出将是:实例1 90%可能是A类,75%可能是B类,60%可能是C类..

谢谢.

Answer 1

Weka的API有一个名为Classifier.distributionForInstance()的方法可用于获取分类预测分布.然后,您可以通过降低概率来对分布进行排序,以获得前N个预测.

下面是打印出的函数:(1)测试实例的地面实况标签; (2)来自classifyInstance()的预测标签; (3)来自distributionForInstance()的预测分布.我已经将它用于J48,但它应该与其他分类器一起使用.

输入参数是序列化模型文件(您可以在模型训练阶段创建并应用-d选项)和ARFF格式的测试文件.

public void test(String modelFileSerialized, String testFileARFF) 
    throws Exception
{
    // Deserialize the classifier.
    Classifier classifier = 
        (Classifier) weka.core.SerializationHelper.read(
            modelFileSerialized);

    // Load the test instances.
    Instances testInstances = DataSource.read(testFileARFF);

    // Mark the last attribute in each instance as the true class.
    testInstances.setClassIndex(testInstances.numAttributes()-1);

    int numTestInstances = testInstances.numInstances();
    System.out.printf("There are %d test instances\n", numTestInstances);

    // Loop over each test instance.
    for (int i = 0; i < numTestInstances; i++)
    {
        // Get the true class label from the instance's own classIndex.
        String trueClassLabel = 
            testInstances.instance(i).toString(testInstances.classIndex());

        // Make the prediction here.
        double predictionIndex = 
            classifier.classifyInstance(testInstances.instance(i)); 

        // Get the predicted class label from the predictionIndex.
        String predictedClassLabel =
            testInstances.classAttribute().value((int) predictionIndex);

        // Get the prediction probability distribution.
        double[] predictionDistribution = 
            classifier.distributionForInstance(testInstances.instance(i)); 

        // Print out the true label, predicted label, and the distribution.
        System.out.printf("%5d: true=%-10s, predicted=%-10s, distribution=", 
                          i, trueClassLabel, predictedClassLabel); 

        // Loop over all the prediction labels in the distribution.
        for (int predictionDistributionIndex = 0; 
             predictionDistributionIndex < predictionDistribution.length; 
             predictionDistributionIndex++)
        {
            // Get this distribution index's class label.
            String predictionDistributionIndexAsClassLabel = 
                testInstances.classAttribute().value(
                    predictionDistributionIndex);

            // Get the probability.
            double predictionProbability = 
                predictionDistribution[predictionDistributionIndex];

            System.out.printf("[%10s : %6.3f]", 
                              predictionDistributionIndexAsClassLabel, 
                              predictionProbability );
        }

        o.printf("\n");
    }
}

Answer 2

我不知道你是否可以本地做到这一点，但你可以获取每个类别的概率，对它们进行排序并取前三个。

您想要的函数是distributionForInstance(Instance instance)返回double[]每个类别的概率。