nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Siemens Community Catalyst Program

The Siemens Community Catalyst program was co-created with our community to acknowledge technology leaders who consistently contribute to the Siemens Community. Nominations are accepted on a rolling basis.

Nominate Now

"Lower accuracy of libsvm in rapidminer vs weka with same parameters"

njasaj

Hi,
I am really getting confused. I used a same data set with same parameters in weka and rapidminer for classification with libsvm. the strange result was that weka accuracy for prediction was 15 percent higher than rapidminer???(I used same C and same kernel and same gamma for rbf kernal).I think there is something wrong with weka. it's accuracy on training set for testing phase is 100%.
Can any body explain it?
Thanks a lot.

Find more posts tagged with

AI Studio

Performance

Weka

Accepted answers

All comments

njasaj

In addition to above i must say that my data set is imbalanced. rapidminer fail to predict the two smaller classes and just predict the largest class
725 188 211
3 1 1
1 0 1

but weka with same parameters gives
729 0 0
124 65 0
111 0 101
I did not use any weight for classes in weka.Help me please and tell me what is wrong with rapidminer?

thank you.

MariusHelf

There are many different implementations of the SVM. If the Weka implementation works better on your data, you can easily integrate Weka with RapidMiner by installing the Weka Extension. For comparing models please remember to cross-validate them - as you know the training error alone is not an indicator on how well the model will work on unseen data.

Best, Marius

MariusHelf

BTW, you should optimize each implementation separately - for different implementations different parameter sets *might* work better.

Fred12

does the Weka LibSVM implementation still exist or was it removed? Somehow I cannot see any LibSVM Weka implementation anymore in the list...? Would like to try it out..

Thomas_Ott

The version of Weka we implement is v3.6.9. But from this: https://weka.wikispaces.com/LibSVM it appears it's a 3rd party tool that needs to be downloaded and installed seperately. It looks like if you want to use the Weka implementaiton of LibSVM, you have to download it extra.

Fred12

thanks, but it seems that the download links are broken..

Thomas_Ott

I can't do anything about that. Maybe contact them, somehow?

Quick Links

Upcoming Events

Advancing power electronics design with Simcenter PSIM and High-Performance Computing
Join us for a community conversation on how High-Performance Computing (HPC) and Simcenter PSIM work together to meet the increasing demands of modern power electronics simulation. During this one-hour technical session, you'll discover how leveraging HPC can speed up simulations, improve scalability, and empower engineers…
Getting Started with Faster Motor Building in Simcenter Simlab
Join us for a community conversation on accelerating your motor simulation workflow with Simcenter Simlab. In this beginner-friendly session, we'll introduce the platform's automated model-building capabilities and show how easy it is to set up your first electric motor analysis. You'll see the basic steps of geometry…
Practical hybrid solver workflows in Simcenter Feko
Join us for a Community Conversation where we'll discuss practical approaches to analyzing complex electromagnetic models using hybrid solver techniques. This session will provide a general overview of how different computational methods can be combined within a single simulation to address models containing varied…

View all community events