Hi, I have problem with my model in weka (j48 cross-validation) that many instances are classified wrong when it comes to the second class. Is there any way to improve it or rather not? I'm not an expert in weka. Thank you in advance. My output is above. In NaiveBayes it presents better but still TP Rate < 0.5 for the second class. NaiveByes weka
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It is hard to reproduce your example with the given information. However the solution is probably to turn your classifiert into a cost sensitive classifier https://weka.wikispaces.com/CostSensitiveClassifier?responseToken=019a566fb2ce3b016b9c8c791c92e8e35
What it does it assigns a higher value to misclassifications of a certain class. In your case this would be the "True" class.
You can also simulate such an algorithm by oversampling your positive examples. This is, if you have
npositive examples you samplek*npositive example, while you keep your negative examples as they are. You could also simply double positive examples.