Huh, cool I didn't know about balance_weights before. I'm also having a
hard time finding documentation on it besides:
"DEPRECATED: balance_weights is an internal function and will be removed in
0.16"
What will it be replaced by in 0.16?
Thanks,
sf
On Wed, Aug 28, 2013 at 4:10 AM, Gilles Loup
mple to see the sample_weights format.
> http://scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html
>
> You can provide different weights to different classes (for e.g.,
> inversely proportional to the number of samples).
>
> -Manish
>
> On Jul 12, 2013, at 4:40 PM, S
I'm dealing with a 50-class classification problem with extremely
unbalanced classes. The smallest class has about 1000 samples and the
largest has 500,000. The random forest I've trained is being heavily
skewed towards the big classes.
Is there a good way to deal with this kind of problem in sk
Whoops, I should have checked that a bit better =)
The regularization needs to be added to "S2" and not "S".
On Sun, Jul 7, 2013 at 4:55 PM, Sergey Feldman wrote:
> Howdy,
>
> I noticed that the sklearn library's QDA doesn't have any regularization. I
Howdy,
I noticed that the sklearn library's QDA doesn't have any regularization. In
my experience, a little convariance regularization can mean the difference
between total failure due to numerical issues and surprisingly
high classification accuracy.
Adding something basic would be as simple as
