[scikit-learn] RFE with logistic regression

[Benoît Presles]

I did the same tests as before adding random_state=0 and:

1. I have got the same problem as before, i.e. when I execute the RFE 
multiple times I don't get the same ranking each time.

2. When I change the solver to 'sag' or 'saga' 
(LogisticRegression(C=1e9, verbose=1, max_iter=10000, 
fit_intercept=False, random_state=0, solver='sag')), it
seems that I get the same results at each run but the ranking is not the 
same between these two solvers.

3. With C=1, it seems that I have the same results at each run for all 
solvers (liblinear, sag and saga), however the ranking is not the same 
between the solvers.

Thanks for your help,
Ben


PS1: I checked and n_iter_ seems to be always lower than max_iter.
PS2: my data is scaled, I am using "StandardScaler".



Le 24/07/2018 à 20:33, Andreas Mueller a écrit :
>
>
> On 07/24/2018 02:07 PM, Benoît Presles wrote:
>> I did the same tests as before adding fit_intercept=False and:
>>
>> 1. I have got the same problem as before, i.e. when I execute the RFE 
>> multiple times I don't get the same ranking each time.
>>
>> 2. When I change the solver to 'sag' 
>> (classifier_RFE=LogisticRegression(C=1e9, verbose=1, max_iter=10000, 
>> fit_intercept=False, solver='sag')), it seems that I get the same 
>> ranking at each run. This is not the case with the 'saga' solver.
>> The ranking is not the same between the solvers.
>>
>> 3. With C=1, it seems that I have the same results at each run for 
>> all solvers (liblinear, sag and saga), however the ranking is not the 
>> same between the solvers.
>>
>>
>> How can I get reproducible and consistent results?
>>
> Did you scale your data? If not, saga and sag will basically fail.
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