Just my 0.02$ as a user: I was also a confused/put-off by `alpha` and
`l1_ratio` when I first explored SGDClassifier, I found those names to
be pretty inconsistent --- plus I tend to call my regularization
parameters `lambda` and use `alpha` for learning rates. I'm sure other
people associate
Hi there!
I've noticed that sklearn uses numpy.linalg instead of scipy.linalg for
its linear algebra implementations (e.g. dot or svd). However I found
that scipy.linalg consistently performs better on my machines. Since
sklearn requires scipy anyways, I was wondering what the reason is for
On 2013-10-19 17:36, Lars Buitinck wrote:
2013/10/19 Thomas Unterthiner thomas.unterthi...@gmx.net:
I've noticed that sklearn uses numpy.linalg instead of scipy.linalg for its
linear algebra implementations (e.g. dot or svd). However I found that
scipy.linalg consistently performs better on my
Hi there!
the http://scikit-learn.org homepage recommends posting on this mailing
list before making major contributions, so here it goes:
sklearn.preprocessing currently offers both a scale() function and a
StandardScaler transformer, as well as a MinMaxScaler.
I'd like to add a
