Dear Sebastian,
Thank you for your response.
Best,
S
.
Loukas Serafeim
University of Geneva
email: [email protected]
2017-03-07 17:56 GMT+01:00 Sebastian Raschka :
> Hi, Loukas and Mahesh,
> for LOOCV, you could e.g., use the LeaveOneOut class
>
>
Hi Sebastian,
Thank you
On 7 Mar 2017 10:28 p.m., "Sebastian Raschka" wrote:
> Hi, Loukas and Mahesh,
> for LOOCV, you could e.g., use the LeaveOneOut class
>
> ```
> from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
> from sklearn.model_selection import LeaveOneOut
>
> loo =
Hi, Loukas and Mahesh,
for LOOCV, you could e.g., use the LeaveOneOut class
```
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import LeaveOneOut
loo = LeaveOneOut()
lda = LinearDiscriminantAnalysis()
test_fold_predictions = []
for train_index,
Dear Mahesh,
Thank you for your response.
I read the documentation however I did not find anything related to
cross-validation (leave one out).
Can you give me a hint?
Thank you,
S
.
Loukas Serafeim
University of Geneva
email: [email protected]
201
Yes. Please see following link:
http://scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysis.html
On Tue, Mar 7, 2017 at 3:18 PM, Serafeim Loukas wrote:
> Dear scikit members,
>
>
> I would like to ask if there is any function that implements
> Linea
