Hi Olivier and Lars, it is very clear now with your informative replies.
Haven't thought about the unbalance in multi-class classification. Thanks a
lot!
On 7 November 2011 23:44, Lars Buitinck <[email protected]> wrote:
> 2011/11/7 SK Sn <[email protected]>:
> > Hi all, I am looking into generating accuracy metrics of a
> classification,
> > in the context of text classification.
> >
> > In API, there is no accuracy directly, I tried two things:
> >
> > 1: accuracy = np.mean(pred.ravel() == y_test.ravel())
>
> This is the usual notion of accuracy. It coincides with our definition
> of recall in the multi-class case, but not in the binary case:
>
> In [1]: y_test = array([0,0,0,1,1,1,0,0,1])
>
> In [2]: pred = array([1,0,0,0,1,1,0,0,1])
>
> In [3]: recall_score(y_test, pred)
> Out[3]: 0.75
>
> In [4]: np.mean(pred == y_test)
> Out[4]: 0.77777777777777779
>
>
> --
> Lars Buitinck
> Scientific programmer, ILPS
> University of Amsterdam
>
>
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