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josejimenezluna / pyGPGO

Bayesian optimization for Python
http://pygpgo.readthedocs.io
MIT License
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Changing DF/nu parameter from default=3.0 #12

Closed CPJClare closed 5 years ago

CPJClare commented 5 years ago

Hello hawk31,

I am probably making an obvious mistake, having unsuccessfully tried to change both the "df" and "nu=3.0" parameters in both 'acquisition.py' and 'tStudentProcess.py' files.

Can you quickly explain how I change this parameter? I would like to see the impact of differing DF on the expected improvement utility function.

Many thanks, ConorC

josejimenezluna commented 5 years ago

Hello @ConorCUIster

It should be enough to set the parameter in the surrogate model itself. 

from pyGPGO.surrogates import tStudentProcess
surr = tStudentProcess(covfunc, nu=3.0)

Can you provide a minimum working example of whatever does not work?

CPJClare commented 5 years ago

José,

Thank you for your reply.

I may be missing something, but I tried changing the nu/DF paramater in the class defintion & I couldn't get the output chart (showing the results of x6 iterations for both the unknown function estimated and the acquisition function) to change.

I created my own code using the nu/DF parameter as a user-defined input variable, which seems to work OK i.e. the variability around the points sampled increases, as nu/DF also increases (all else equal).

Conor

From: José Jiménez notifications@github.com Sent: 16 October 2018 12:48:56 To: hawk31/pyGPGO Cc: Conor Clare; Mention Subject: Re: [hawk31/pyGPGO] Changing DF/nu parameter from default=3.0 (#12)

Hello @ConorCUIsterhttps://github.com/ConorCUIster

It should be enough to set the parameter in the surrogate model itself.

from pyGPGO.surrogates import tStudentProcess surr = tStudentProcess(covfunc, nu=3.0)

Can you provide a minimum working example of whatever does not work?

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