My apologies, there was a typo in the code below, second example, should
read:
train_scores1, test_scores1 = validation_curve(SVC_classifier_LOWO_VC1, X,
y, "C", parm_range1, cv =logo.split(X, y, groups=groups), scoring =
'accuracy')
Everything else is correct.
On Fri, December 2, 2016 10:28 pm
HI all,
I want to plot learning curves on a trained SVM classifier, using a custom
scorer, and using Leave One Group Out as the method of crossvalidation. I
thought I had it figured out, but two different scorers - 'f1_micro' and
'accuracy' - will yield identical values. I am confused, is that sup
Another fun shortcoming of the project interface:
If a card is already present in your project, you can not search for it
(though you can ctrl+f)
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Hey Nelle.
That sounds great. My main question is how you'd expose this to the user.
Will it be a separate website? A bot? Emails? Greasemonkey on top of github?
Most of these could be implemented with tags that are automatically
assigned by a bot, I guess.
That would be quite a few tags, thoug
Hello,
This seems a good moment to say that we will be starting a project at
BIDS next semester to try extract information from github and classify
PRs into different categories (stalled, updated, needs review).
Stéfan drafted a list of elements he would like to see for
scikit-image, and I have be
So did we ever decide on how to prioritize reviews?
(I was still mentally / notification catching up after 0.18.1)
There are some really important issues to tackle, often with proposed
solutions, not no reviews!
It's hard for everybody to keep the big picture in mind with such a full
issue trac
