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I was able to successfully build and run go-pge. However, I have a few simple questions:
We would like to include PGE in a comparative study but we need to be able to run experiments successfully. What we need is to be able to provide the algorithm training data, let it crunch the numbers and then retrieve the final model or a set of models along with their training and testing performance using RMSE, or at least retrieve the models in a form that can be parsed and reused. However, go-pge (or rather scripts/test.sh) produces a bunch of files but it is by far not clear what is exactly contained in each file and what do the numbers mean. I can guess some of it based on the file names but it's only a guess. Could you provide some pointers as to where can we obtain these outputs?
What is the relation of go-pge and https://github.com/verdverm/pypge regarding the algorithm? Is go-pge the same algorithm as pypge for explicit problems? For our study, we like this go version a bit more as it does not involve multiple docker containers and has much more straightforward usage but the outputs are much less readable (hence the first question). However, pypge's outputs are not easy do read too. If pypge is the way to go, we have started a similar issue there: Explanation of outputs pypge#12
If you could provide an answer the questions we would be happy to include your algorithm to our study and cite your paper.
The text was updated successfully, but these errors were encountered:
Don't use this project, there are errors in the algebra system. PyPGE is the same algorithm with correct formula simplification. I'll respond further in your other issue on pypge
I was able to successfully build and run go-pge. However, I have a few simple questions:
If you could provide an answer the questions we would be happy to include your algorithm to our study and cite your paper.
The text was updated successfully, but these errors were encountered: