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m Class Hierarchy (jlibsvm SNAPSHOT API)

So there is no need for a manually 1vsN approach. BheeMa BheeMa jliibsvm 3 gold badges 11 11 silver badges 29 29 bronze badges. Post as a guest Name. This is how I am doing. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. But I am getting the same jliibsvm probability for every sentence in the test set for all models. By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

Active 2 years, 7 months ago. Sign up using Email and Password. How to get jlibsvm prediction probability in multi-class classification Ask Question.

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jlibsvm

The following is how I set parameters for training: A total of 75 sentences, In which 25 sentences belongs to each class. You are getting the same output, because you generate the same model three times.

If it detects, that more than two class labes are provided in the given data, it automatically performs multiclass classification. I have a comparatively small train jlibbsvm.

jlibsvm

The reason for this is, that jlibsvm is able to perform multiclass classification out of the box based on the provided data LIBSVM itself supports this too. I am using jlibsvm for a multi-class classification problem. Email Required, but never shown. Is there any other better way to do multi-class classification other than this? I am new to SVM. How do we handle problem users? A lot has changed.

Index of /repositories/snapshots/edu/berkeley/compbio/jlibsvm

Sign up or log in Sign up using Google. Sign up using Facebook. Basically, I am doing a sentence classification problem.

jlibsvm

Just supply the data with class-labels for each category. Which one returns the highest will be the class the sentence belong to. What I understood is I am doing One-against-all classification. I’m resigning as a moderator from all Stack Exchange sites, effective today.

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Index of /repositories/releases/edu/berkeley/compbio/jlibsvm/0.902

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While testing, to get the true label of a sentence, I am giving the sentence to 3 models and I am taking the prediction probability returned by these 3 models. There are 3 Classes.