Re: [Scikit-learn-general] classification metrics understanding

[Joel Nothman]

If you are treating your Logistic Regression output as binary (i.e. not
using predict_proba or decision_function), could you please provide the
confusion matrix?

On 26 November 2015 at 05:06, Herbert Schulz  wrote:

> Hi, i think i have some "missunderstanding" due to the classification
> metric in scikit-learn
>
>
>
> i have a 2 class problem it is 1.0 or  2.0
>
>
>  precisionrecall  f1-score   support
>
> 1.0   0.86  0.76  0.81   254
> 2.0   0.49  0.65  0.5691
>
> avg / total   0.76  0.73  0.74   345
>
>
> Specificity: [ 1.*  0.35164835*  0.]
> recall,tpr,sensitivity  [ 0. * 0.24015748*  1.]
>
>
> # this part is manually computed  ( precision, sens, spec, ballanced
> accuracy )
>
> logistic regression 0.86,* 0.76, 0.65,* 0.7
>
>
>
> The   part with:
>
> Specificity: [ 1.  0.35164835  0.]
> recall,tpr,sensitivity  [ 0.  0.24015748  1.]
>
> are computed with
>
> fpr, tpr, thresholds = metrics.roc_curve(expected, predi,
> pos_label=1)
> print "Specificity:", 1-fpr
> print "recall,tpr,sensitivity",tpr
>
> Why is th speceficity for 1-fpr  are computed wtih [ 1.
> 0.35164835  0.]
>
> and not 0.65 ?
>
> Same with recall
>
>
>
>
>
>
>
>
>
>
>
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[Scikit-learn-general] classification metrics understanding

[Herbert Schulz]

Hi, i think i have some "missunderstanding" due to the classification
metric in scikit-learn



i have a 2 class problem it is 1.0 or  2.0


 precisionrecall  f1-score   support

1.0   0.86  0.76  0.81   254
2.0   0.49  0.65  0.5691

avg / total   0.76  0.73  0.74   345


Specificity: [ 1.*  0.35164835*  0.]
recall,tpr,sensitivity  [ 0. * 0.24015748*  1.]


# this part is manually computed  ( precision, sens, spec, ballanced
accuracy )

logistic regression 0.86,* 0.76, 0.65,* 0.7



The   part with:

Specificity: [ 1.  0.35164835  0.]
recall,tpr,sensitivity  [ 0.  0.24015748  1.]

are computed with

fpr, tpr, thresholds = metrics.roc_curve(expected, predi,
pos_label=1)
print "Specificity:", 1-fpr
print "recall,tpr,sensitivity",tpr

Why is th speceficity for 1-fpr  are computed wtih [ 1.
0.35164835  0.]

and not 0.65 ?

Same with recall
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