i) I think in practice, this scenario is highly unlikely (floating points), but
I am pretty sure it would be the class with the lower integer index (due to
argmax).
ii) general question: is one class over- or underrepresented? I assume you
already did some grid searching and it's the best you could get? Maybe try a
different classifier or over-/undersampling techniqyes
iii) Why, not, and I think the random forest classifier should be well
calibrated, too.
iv) Use k-fold cross validation.
(http://scikit-learn.org/stable/modules/cross_validation.html)
Best,
Sebastian
> On Feb 26, 2015, at 8:00 AM, shalu jhanwar <shalu.jhanwa...@gmail.com> wrote:
>
> Hey guys,
>
> Would you like to comment on them according to your exp.?
>
> i) if both the classes are having same probability (0.5), then which class
> would be predicted by Random Forest?
> ii) In my classification, I have seen more false predictions corresponding to
> the positive class by my model. Can you suggest how can I improve the
> accuracy of the model by tuning any of the parameter or any suggestion?
> iii) Can I use these probability values to rank my predictions (strong and
> weak predictions)?
> iv) How can I check if my model is overfit or not?
>
> Many thanks!
> Shalu
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