It's not a very clear error message, and PR#2278 corrected that. "The sum
of true positives and false positives" for some label l is the number of
times your system predicts l in the fold's test data. So it's certainly
possible that this will occur, no matter what CV strategy you take. A
stratified
2013/10/17 Josh Wasserstein :
> Hi Joel and others,
>
> Sorry, but I am still confused.. If I am using stratified shuffle splitting,
> shouldn't I always have some positives in the testing set (I have positives
> in the full dataset)? The message says: "The sum of true positives and false
> positiv
Hi Joel and others,
Sorry, but I am still confused.. If I am using *stratified shuffle splitting
*, shouldn't I always have *some positives in the testing set (I have
positives in the full dataset)*? The message says: "The sum of true
positives and false positives (in other words total # of posit
2013/10/16 Carlos Aspillaga :
> Hello guys,
>
> I've been using scikit-learn for a while and I would like to contribute some
> new functionalities. I have them implemented in other languages, but not in
> python (yet...)
> To start, I would love to implement some classic Feature Selection
> Algorit
Hi Carlos,
Welcome! We'd love to have you contribute. You can start by reading
through the developers guide on our website, and following the suggestions
there: http://scikit-learn.org/stable/developers/
Feel free to ask here if any questions come up,
Jake
On Wed, Oct 16, 2013 at 2:09 PM, Ca
Hello guys,
I've been using scikit-learn for a while and I would like to contribute
some new functionalities. I have them implemented in other languages, but
not in python (yet...)
To start, I would love to implement some classic Feature Selection
Algorithms (dimensionality reduction) that I have
