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Asked: 2026-05-13T00:39:34+00:00

I’m using the explorer feature of Weka for classification. So I have my .arff

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I’m using the explorer feature of Weka for classification.

So I have my .arff file, with 2 features of NUMERIC value, and my class is a binary 0 or 1 (eg {0,1}).

Sample:

@RELATION summary
@ATTRIBUTE feature1 NUMERIC
@ATTRIBUTE feature2 NUMERIC
@ATTRIBUTE class {1,0}

@DATA
23,11,0
20,100,1
2,36,0
98,8,1
.....

I load this .arff file, use 10-fold cross validation (no test file), and choose NaiveBayes, then I classify the data, and it gives me: 5 incorrectly labeled, 100 correctly labeled. So far so good.

Now, I significantly change my .arff file (give completely random values for my feature attributes). And repeat the above, and I get the EXACT same statistics when classifying.

I tried this with more changes to my .arff file, different classification algorithms. Still, EXACT same statistic (within the same algorithm) no matter what values I give to my .arff file.

Am I doing something wrong here?

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1 Answer

  1. Editorial Team

    It’s hard to tell without more information, but I have two suggestions:

    1. What are the relative proportions of the two classes? Is it 5 to 100? Lots of algorithms don’t work well with highly skewed class label distributions.

    2. Just a hunch, but try changing your class labels from numbers to strings (e.g. ‘class1’ and ‘class2’). Weka calls these ‘nominal’ attributes so maybe using numbers is not allowed.

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