Comments (4)
@ktamiola should probably tackle this one.
briefly here from me: we have shifted the original scale from -1,1 by +2, so it's now 1 for beta sheet, 2 for random-coil and 3 for helix. 0 now indicates no data for a given sequence position.
@ErmiaAzarkhalili many thank for reporting this inconsistency, you're obviously correct, we'll get it sorted asap
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Dear @ErmiaAzarkhalili , indeed I have mistakenly used in our README.md
an old functional propensity scale. We have shifted all the data by 2.0
as Keras and Tensorflow can't handle np.nan
in loss and gradient computation procedures. Thank you for reporting this serious discrepancy.
from dspp-keras.
@ktamiola @jandom Thanks for the quick update. could you please update the README.md
file?
from dspp-keras.
Absolutely! The README.md
file has been updated already!
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Related Issues (19)
- JSON instead of cPickle HOT 1
- Negative CHI2 HOT 2
- Abnormal Y values HOT 2
- Add support for muti-GPU traning HOT 1
- Batch size affects metrics (chi2, rmsd) HOT 3
- Embedding with 0 masking HOT 2
- Decoder needed HOT 1
- Obsolete Keras API in multi-GPU code HOT 1
- Incomplete README.md HOT 3
- Restart functionality HOT 2
- Correct LICENSE
- Error to Download data with Python3 HOT 4
- How to get Structural disorder probability in keras API HOT 5
- 800 trong biểu đồ kết quả ở plot.png có ý nghĩa là gì? HOT 1
- Ridiculously slow caching time for raw data
- Outdated dspp-keras pip package HOT 1
- Suspiciously high CHI2 HOT 1
- h5py dependency HOT 1
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