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Precision, Recall and F1 Metrics Removed #5794
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Yes, it was intentional. See https://github.com/fchollet/keras/wiki/Keras-2.0-release-notes |
Ah missed that, thank you very much. |
What was the reason behind removing them? |
Basically these are all global metrics that were approximated
batch-wise, which is more misleading than helpful. This was mentioned in
the docs but it's much cleaner to remove them altogether. It was a mistake
to merge them in the first place.
…On 19 March 2017 at 11:28, Jacek Karwowski ***@***.***> wrote:
What was the reason behind removing them?
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@fchollet Are there any plans to add another implementation for these metrics (evaluated globally) ? |
@karimpedia What I did was creating a Callback and calculate them on the end of each epoch with the validation data.
And implement a function that calculates the f1 score or instead use Scikit Learn's Fscore function. |
@imanoluria, i was using your code (thanks for posting it BTW) with the sklearn's F1 in my model. the model has 3 inputs and one output.
the fit portion:
my input to the validation is (first dim is #samples): my model's output is a one hot 25 category vector... can you see what's the problem? thanks a lot! @fchollet - will there be a future innate API for metrics in check pointer / similar method? |
Hi @basque21, I tried to extend your example to work with The error I got was My code snippet is below:
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@ShiangYong Did you set |
Em sex, 20 de abr de 2018 às 2:11 AM, Daniel Klevebring <
notifications@github.com> escreveu:
@ShiangYong <https://github.com/ShiangYong> Did you set validation_data
when you fit()?
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no
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@dakl No, I need to use |
If someone needs to implement it I suggest this work-around:
Something like this:
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It appears Precision, Recall and F1 metrics have been removed from metrics.py as of today but I couldn't find any reference to their removal in the commit logs. Was this intentional?
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