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Author Topic: Klassifikation with SVM  (Read 1505 times)
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« on: July 10, 2008, 12:34:37 PM »

Hi,

i am trying to classify a data set with help of the JMySVMLearner. Now i've the following problem:

With GridParameterOptimization i can only find a parameter set for which the classification result for one class ist correct (100%) and for the other class very bad (<=30%).
Is it possible to find a parameter set for which you can obtain a balanced classification result (>=75% for each class)?

Thanks in advance.

Barbara
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haddock
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« Reply #1 on: July 10, 2008, 01:42:37 PM »

Hi Barbara,

You can attempt to tilt the SVM learning by wrapping it in a MetaCost operator. In this case you would increase the costs of misclassifying the second class, in the hope that a more balanced performance emerges. Works fine on binominal labels, not confident about polynominals. Also I've found that performance can change quite a bit depending on the correct settings for C and gamma in the libSVM learner.

Good weekend to all miners!

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