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JamesRitchie / scikit-rvm

Relevance Vector Machine implementation using the scikit-learn API.
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Getting the confidence of the prediction? #10

Open jandono opened 7 years ago

jandono commented 7 years ago

Hello James,

when using Relevance Vector Regression, is it possible to somehow get the confidence of the predictions? For example lets say that my regression model outputs some predictions, what I want to know is how sure my regression model is that those predictions are true.

Kind regards, ac1dxtrem

Blair-Young commented 7 years ago

I too am interested in this issue, I noticed you have a predict_proba function but I'm unsure how to use it.

stbedoya commented 7 years ago

Hello guys,

I have the same problem with the prediction of probabilities. Could you guys solve your problem?

Thanks!

Sandy4321 commented 6 years ago

me too

Spandyie commented 6 years ago

Correct if I am wrong but , the mean and standard deviation can be extracted using instance_variable.sigma_and instance_variable.m_ , isnt it ?

JamesRitchie commented 6 years ago

m_ and sigma_ are parameters of the weights, not the prediction.

I think if you call predict on the regression class with eval_MSE=True you'll get the standard deviation returned along with the mean as a tuple. I copied this convention from scikit-learn, but they've since changed it to return_std, which makes more sense. If I can get around to fixing up this package I'll check it and change it.

Sandy4321 commented 4 years ago

And what is about returning probability for confidence?

woctezuma commented 4 years ago

For your information, there is another package for RVM, following scikit-learn conventions as well:

https://github.com/Mind-the-Pineapple/sklearn-rvm

You can see that return_std is accepted:

plot

Reference: https://sklearn-rvm.readthedocs.io/en/latest/auto_examples/plot_compare_rvr_svr.html