ONE CLASS

[matus-pikuliak]

Hey,
I am trying to use your gem to make one-class svm work. I was just trying to make it work with the modified example code:

problem = Libsvm::Problem.new

parameter = Libsvm::SvmParameter.new
parameter.cache_size = 1 # in megabytes
parameter.eps = 0.001
parameter.nu = 0.5
parameter.svm_type = Libsvm::SvmType::ONE_CLASS

examples = [ [1,1,1], [0,0,0] ].map {|ary| Libsvm::Node.features(ary) }
labels = [1,1]
problem.set_examples(labels, examples)

model = Libsvm::Model.train(problem, parameter)

puts model.predict(Libsvm::Node.features(1, 1, 1))
puts model.predict(Libsvm::Node.features(0, 0, 0))
puts model.predict(Libsvm::Node.features(100, 100, 100))

However the output is -1 -1 -1 insted of 1 1 -1 as I would expect. What am I doing wrong?

[febeling]

If you're just getting started with SVM usage your best bet is probably exploring by using larger data sets and graphing them continuously while changing the parameters.

Or if you think it's a bug it would be helpful to have an example using LIBSVM via command line tools or another binding in order to compare where results diverge.

[pbssubhash]

@matus-pikuliak Did it work?

I see the same error and can't a reliable way out! Did you get a chance to find the solution? If yes, could you please share..

@febeling : Isn't there official support for One Class classification for this Ruby wrapper?

Thanks.

[febeling]

@pbssubhash Nothing in this library prevents you from using one-class configuration.

[pbssubhash]

@febeling
So, how do I go about configuring it for One class?
Is it the same way used in the example?

Thanks.

[febeling]

sorry, I didn't use that feature in a long time, so I can't give you details.

…

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On 28 Feb 2017, at 16:28, P B Surya Subhash ***@***.***> wrote: @febeling So, how do I go about configuring it for One class? Is it the same way used in the example? Thanks. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or mute the thread.