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is clearly suspect since the naive method is giving an AUC around 0 and not 50. I believe the issue is that the results dictionary gives the metrics on a scale from [0,1], while the baseline models give the metrics on a scale of [0,100]. I can't actually find in the code where these baseline results are scaled by 100, or else I would happily make a pull request. In general, I think it would be easier to keep everything on a scale of [0,1]
The text was updated successfully, but these errors were encountered:
Thanks for your issue @mc-robinson! You are right, the baselines results are in the range [0, 100], while the tf.keras.metrics for AUC and Accuracy in the range [0, 1]. We are fixing it in the next release, by rescaling baselines in [0, 1].
I could be wrong, but this plot for example
is clearly suspect since the naive method is giving an AUC around 0 and not 50. I believe the issue is that the
results
dictionary gives the metrics on a scale from [0,1], while the baseline models give the metrics on a scale of [0,100]. I can't actually find in the code where these baseline results are scaled by 100, or else I would happily make a pull request. In general, I think it would be easier to keep everything on a scale of [0,1]The text was updated successfully, but these errors were encountered: