I tried pack-pad technique. It does reduce many computing time a lot, but my accuracy is significantly worse than former one.
It sounds make sense with approximation theory that keep longer computing time you will get more fine value. But this time it is neural network. I don't think training by embedded zero vector will get me more accuracy. Please correct me if I am wrong.
Here is my files. If you would like to see my code.
This is plain one with 50% accuracy
It is not a homework assignment. It is my self-study.
Questions:
1. Am I get a correct result?
2. Does pack-pad sacrifices accuracy?
PS:
I feel my question would fit to stackoverflow most than Datascience or CodeReview. Please let me move it if need.
