Hi Sebastian,
Sorry, I used the wrong terms (I was referring to algo as model).. great
then, i think what i have is aligned with your workflow..
Thank you very much for your help!
Have a good weekend,
Raga
On Fri, Jan 27, 2017 at 1:01 PM, Sebastian Raschka
wrote:
> Hi, Raga,
>
> sounds good,
Hi, Raga,
sounds good, but I am wondering a bit about the order. 2) should come before
1), right? Because model selection is basically done via hyperparam
optimization.
Not saying that this is the optimal/right approach, but I usually do it like
this:
1.) algo selection via nested cv
2.) mode
Hi, Raga,
sounds good, but I am wondering a bit about the order. 2) should come before
1), right? Because model selection is basically done via hyperparam
optimization.
Not saying that this is the optimal/right approach, but I usually do it like
this:
1.) algo selection via nested cv
2.) mode
Sounds good, Sebastian.. thanks for the suggestions..
My dataset is relatively small (only ~35 samples), and this is the workflow
I have set up so far..
1. Model selection: use nested loop using
cross_val_score(GridSearchCV(...),...) same as shown in the scikit-learn
page that you provided - the r
