Output modification

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Output modification

Alexander Osherenko

I wonder, is it possible to modify the classifier output presented on the WEKA console. For instance, is it possible to add the classwise precision P and recall R values after the calculated confusion matrix 


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where N is the number of outcome values of classification.


Best, Alexander


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Re: Output modification

Eibe Frank-2
Administrator
Yes, it’s possible to add additional plug-in evaluation measures. However, there is currently no plug-in for the straight average of the precision/recall values across classes.

Note that WEKA outputs the *weighted* average (weighted by class size) by default. Here is the output for the iris data:

=== Detailed Accuracy By Class ===

                 TP Rate  FP Rate  Precision  Recall   F-Measure  MCC      ROC Area  PRC Area  Class
                 0.980    0.000    1.000      0.980    0.990      0.985    0.990     0.987     Iris-setosa
                 0.940    0.030    0.940      0.940    0.940      0.910    0.952     0.880     Iris-versicolor
                 0.960    0.030    0.941      0.960    0.950      0.925    0.961     0.905     Iris-virginica
Weighted Avg.    0.960    0.020    0.960      0.960    0.960      0.940    0.968     0.924     

The six per-class precision and recall values are shown, along with their weighted average at the bottom. Because all classes are equally populous in the iris data, the weighted average is equal to the straight average in this case.

Cheers,
Eibe


On 22/05/2017, at 2:30 AM, Alexander Osherenko <[hidden email]> wrote:

I wonder, is it possible to modify the classifier output presented on the WEKA console. For instance, is it possible to add the classwise precision P and recall R values after the calculated confusion matrix 

<image.png>
where N is the number of outcome values of classification.

Best, Alexander
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