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Author Topic: Klassifikation with SVM  (Read 1822 times)
« on: July 10, 2008, 12:34:37 PM »


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.

Hero Member
Posts: 887

« 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!


Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?

T.S.Eliot ~ Choruses from the Rock 1934
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