[R-sig-eco] R-sig-ecology Digest, Vol 132, Issue 10

[Lara Silva]

Prof Dr. Ralf Schäfer

thank you for sharing the links.

Best regards,

Lara Silva

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Ralf Schäfer <schaefer-ralf using uni-landau.de> escreveu no dia sexta,
22/03/2019 à(s) 11:30:

> Hi Lara,
>
> I am actually not sure that this is the best way to proceed.
> Cross-validation seems the method of choice and depending on your purpose
> you can compare the prediction error between models.
> See: Hauenstein S., Wood S.N. & Dormann C.F. (2018). Computing AIC for
> black-box models using generalized degrees of freedom: A comparison with
> cross-validation. *Communications in Statistics - Simulation and
> Computation* *47*, 1382–1396.
> https://doi.org/10.1080/03610918.2017.1315728
>
> However, these authors provide code to derive an AIC for different machine
> learning approaches. https://github.com/biometry/GDF
>
> Hope this helps and have a nice weekend.
>
> Best regards,
>
> Ralf Schäfer
>
> ------------------------------------------------------------
>
> Prof. Dr. Ralf Bernhard Schäfer
> Professor for Quantitative Landscape Ecology
> Environmental Scientist (M.Sc.)
> Institute for Environmental Sciences
> University Koblenz-Landau
> Fortstrasse 7
> 76829 Landau
> Germany
> Mail: schaefer-ralf using uni-landau.de
> Phone: ++49 (0) 6341 280-31536
> Web: www.landscapecology.uni-landau.de
>
> Am 22.03.2019 um 12:00 schrieb r-sig-ecology-request using r-project.org:
>
>
> Message: 1
> Date: Thu, 21 Mar 2019 12:40:54 -0100
> From: Lara Silva <lara.sfp.silva using gmail.com>
> To: r-sig-ecology using r-project.org
> Subject: [R-sig-eco] Calculate AIC, DIC and BIC for models machine
> learning
> Message-ID:
> <CALN9TETOhnxS6OuBZhMT6_YFRggND5Zf9zLkkk5icpN4UbSVTg using mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hello everyone!
>
> In R, it is possible to calculate AIC, DIC, or BIC  for models machine
> learning, like RF, ANN, GBM, MARS?
>
> Are there any functions or specific packages in R?
>
> Any suggestion?
>
> Thanks
>
> Lara
>
>
>
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