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Running trained models on different data #1
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Hi Klaus, The bad news is that we did not save the models so you will have to re-run things. Before getting to into the how to generate and save models, i strongly suggest to choose the "safe1" solution. It only involves a subset of 8 level2 models, and the performance does not change that much. It will be much faster to run. Most of the change are concerning level1 models. I assume your new data are in the same format as the other ones, so here we go :
If you want to save models, you could use the guideline provided by sklearn : http://scikit-learn.org/stable/modules/model_persistence.html For lvl1, you will have to save pre-processing model, post-preprocessing, and final classifyer. for lvl2, you just need to save the classifyer |
When I try to run the code, I get an IndexError: list index is out of range Traceback (most recent call last): |
@ut33 were you able to figure out how to resolve this issue |
I've reproduced the results and verified that they are fine. However I'd like to run the trained models on some new data, and I can't seem to make that work. Maybe you could point me in the right direction? Is it at all possible without retraining everything, because to me it seems you didn't store any trained models, only their predictions.
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