Incorrect class prediction using Weka

Question

I am using the WEKA API weka-stable-3.8.1.
I have been trying to use J48 decision tree(C4.5 implementation of weka). My data has around 22 features and a nominal class with 2 possible values : yes or no.
While evaluating with the following code :

Classifier model = (Classifier) weka.core.SerializationHelper.read(trainedModelDestination);
Evaluation evaluation = new Evaluation(trainingInstances);
evaluation.evaluateModel(model, testingInstances);
System.out.println("Number of correct predictions : "+evaluation.correct());

I get all predictions correct. But when I try these test cases individually using :

for(Instance i : testingInstances){
    double predictedClassLabel = model.classifyInstance(i);
    System.out.println("predictedClassLabel : "+predictedClassLabel);
}

I always get the same output, i.e. 0.0.

Why is this happening ?

that's the predicted class label 0, maybe your testing instance only contain class label 0 and thus everything is correct. — Thomas Jungblut
Na, I tried with different test cases with known results. Also tried instances from trained set. — YetAnotherBot
May be your test instances are totally differents from train instances. Have you tried to evaluate your model on your train set? — Istvan Nagy
In this case, your model trained your dataset. May I ask how big is your training and test data? — Istvan Nagy

Walter Walter · Accepted Answer · 2017-07-04T20:23:45

If the provided snippet is indeed from your code, you seem to be always classifying the first test instance: "testingInstances.firstInstance()".

Rather, you may want to make a loop to classify each test instance.

for(Instance i : testingInstances){
    double predictedClassLabel = model.classifyInstance(i);
    System.out.println("predictedClassLabel : "+predictedClassLabel);
}

Incorrect class prediction using Weka

2 Answers