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[NON-ISSUE] Cross validating training result #5
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Hi @louisgv, your results seem fairly consistent with my training/test accuracy (~86%). I will be working on a deep-model extension to this project this weekend (hopefully), and I will report my findings. It seems that creators of this data set reported 69.71% ± 1.47% (see table 3 from here) accuracy using an OPIUM-based model, so this method beats that already. I have no benchmark for state-of-the-art (I would assume that >95% could be achieved using DCNNs). I will leave this thread open for people to report any model progress or accuracy improvements. Thanks for your interest! EDIT: |
thanks |
Hello @jamesyzhb, please open a new issue on the repository, but I believe it is an issue with a version mismatch with this code and Keras. What version of Keras and TensorFlow/Theano are you using? |
Is a FLask version issue, thanks for the reminder |
Hello,
I would like to cross validate my loss and accuracy with other. Below is my result:
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