"SVM Question"

Ghostrider

I am trying to use an SVM for the first time. Here is my setup:





< output/>
<宏/ >

< operator activated="true" class="process" compatibility="5.1.001" expanded="true" name="Process">

< operator activated="true" class="retrieve" compatibility="5.1.001" expanded="true" height="60" name="Retrieve" width="90" x="112" y="165">


< operator activated="true" class="support_vector_machine_libsvm" compatibility="5.1.001" expanded="true" height="76" name="SVM" width="90" x="246" y="165">


< operator activated="true" class="apply_model" compatibility="5.1.001" expanded="true" height="76" name="Apply Model" width="90" x="380" y="165">


< operator activated="true" class="performance" compatibility="5.1.001" expanded="true" height="76" name="Performance" width="90" x="514" y="165"/>











I am just trying to apply my model to the training data in hopes of seeing very high prediction...after that I plan to examine more complicated / useful cases. But my predictions are very poor. How do I improve the performance of SVM learning? I have heard / can learn parameter optimization, but isn't there some strictness setting that will at least result in 100% accuracy given though support vectors?

haddock

From the link in the SVM Learner help you will see that you need to optimise the parameters ( as in the meta-01 sample ).