Sounds like you got it to me, but perhaps "because theoretically it's
wrong" needs another moment's explanation: your estimator is fitted to the
feature values as they are adjusted in training, so it's inappropriate to
adjust them differently at test time. It's also inappropriate because in
the rea
Thank you! It's clear! Please, tell me if I understood correctly (or I'm
completely stupid):
it took the training set and calculate the mean and the standard deviation for
each feature. To calculate it just substract the mean and divide by the std
(saw in the posted link on stackoverflow);transf
A related question was recently asked recently on Stack Overflow. Does this
help?
http://stackoverflow.com/questions/16137816/scikit-learn-preprocessing-svm-with-multiple-classes-in-a-pipeline
On Tue, May 28, 2013 at 12:18 AM, Gianni Iannelli wrote:
> Found it! But now it has a different name: S
2013/5/27 Gianni Iannelli :
> Found it! But now it has a different name: StandardScaler.
Ah, yes, excuse me.
> Could you please exlpain to me what its the point to store Mean and Standard
> Deviation? It's not so clear to me. And how the transform is made? Sorry for
> my lower knowledge level abo
Found it! But now it has a different name: StandardScaler.
The documentation is here:
http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html#sklearn.preprocessing.StandardScaler
Furthermore, I was reading the documentation:
Centering and scaling happen indepentl
2013/5/27 Gianni Iannelli :
> I was trying the scaler() but Python say to me that doesn't exist. Could
> you please tell me where I wrong? And I could not find also the transform
> method.
from sklearn.preprocessing import Scaler
(with a capital S)
--
Lars Buitinck
Scientific programmer, ILPS
Thanks for the answers!
I was trying the scaler() but Python say to me that doesn't exist. Could you
please tell me where I wrong? And I could not find also the transform method.
Thanks in advance for your answer! Solimyr
From: amuel...@ais.uni-bonn.de
Date: Sat, 25 May 2013 19:11:06 +0200
To: s
Here it is: https://github.com/scikit-learn/scikit-learn/pull/2004
E/
2013/5/24 Eustache DIEMERT
> I've come up with a first version in a binary setting.
>
> Here is the main file :
> https://github.com/oddskool/scikit-learn/blob/out-of-core-examples/examples/out_of_core_classification.py
>
>
