Well done guys! Thanks a lot for this great release! I hope to be back soon.
Best,
Chris
On Fri, Aug 25, 2017 at 3:14 AM, Guillaume Lemaître
wrote:
> We are excited to announce the new release of the scikit-learn-contrib
> imbalanced-learn, already available through conda and pip (cf. the
> ins
In drug discovery, if you are lucky you might get hit compounds 10% of the
time.
So if you do ML-based drug discovery, your datasets are strongly imbalanced.
It seems the imbalanced package would be perfect for this area.
J.B.
2017-08-25 10:53 GMT+02:00 Jaques Grobler :
> Congrats guys!
>
> 2017
Congrats guys!
2017-08-25 8:18 GMT+02:00 Sebastian Raschka :
> Just read through the summary of the new features and browsed through the
> user guide. The guide is really well structured and easy to navigate,
> thanks for putting all the work into it. Overall, thanks for this great
> contribution
Just read through the summary of the new features and browsed through the user
guide. The guide is really well structured and easy to navigate, thanks for
putting all the work into it. Overall, thanks for this great contribution and
new version :)
Best,
Sebastian
> On Aug 24, 2017, at 8:14 PM,
+1 B
On 25/08/2017 07:52, Gael Varoquaux wrote:
Indeed, congratulations for the release!
Gaël
On Fri, Aug 25, 2017 at 02:13:26PM +1000, Joel Nothman wrote:
Congratulations Guillaume and the imblearn team!
On 25 August 2017 at 10:14, Guillaume Lemaître wrote:
We are excited to announce t
Indeed, congratulations for the release!
Gaël
On Fri, Aug 25, 2017 at 02:13:26PM +1000, Joel Nothman wrote:
> Congratulations Guillaume and the imblearn team!
> On 25 August 2017 at 10:14, Guillaume Lemaître wrote:
> We are excited to announce the new release of the scikit-learn-contrib
>
Congratulations Guillaume and the imblearn team!
On 25 August 2017 at 10:14, Guillaume Lemaître
wrote:
> We are excited to announce the new release of the scikit-learn-contrib
> imbalanced-learn, already available through conda and pip (cf. the
> installation page https://tinyurl.com/y92flbab fo
erry 10 Darkphone
> *From: *Guillaume Lemaître
> *Sent: *Thursday, August 24, 2017 20:15
> *To: *Scikit-learn user and developer mailing list
> *Reply To: *Scikit-learn mailing list
> *Subject: *[scikit-learn] imbalanced-learn 0.3.0 is chasing scikit-learn
> 0.19.0
>
> We are
Merci beaucoup. Super utile. J' ai d'ailleurs introduit ton module a la conference data intelligence a Capital One il y a moins de 2 mois ( en banlieue de Washington DC).
We are excited to announce the new release of the scikit-learn-contrib
imbalanced-learn, already available through conda and pip (cf. the
installation page https://tinyurl.com/y92flbab for more info)
Notable add-ons are:
* Support of sparse matrices
* Support of multi-class resampling for all met
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