I don't think I can provide the data, but I'm trying to create some
simulated data that produces a similar difference.
I was just messing with R, and for LDA got a different result from the
other 2. I wonder if its just something I am doing wrong.
On Thu, Feb 14, 2013 at 10:07 AM, Andreas Mueller
<[email protected]>wrote:
> On 02/14/2013 04:04 PM, Andreas Mueller wrote:
> > On 02/14/2013 03:59 PM, David Reed wrote:
> >> I dont think this is the problem. My data is definetly oversampled, I
> >> have 5000 samples for the 1 feature.
> >>
> >> I also should say that the problem that led be to LDA was seeing there
> >> was a large bias between SVM classification accuracy in sklearn and
> >> matlab. I am using the same parameters on both, and again testing on
> >> my training. Using the same univariate data set, I see 0.63 from
> >> matlab and 0.58 from sklearn.
> >>
> > Which version of scikit-learn are you using? Are you using sparse
> matrices?
> > There was a weird bug in using sparse matrices and SVMs in an earlier
> > version of sklearn.
> > If there is still a discrepancy in either of the algorithms, we must
> > investigate!
> >
> Would it be possible to provide your data or even better, some small
> dataset
> to reproduce the discrepancy?
>
>
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