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License: MIT License
Virtual screening on PriA-SSB and RMI-FANCM with the LifeChem library
License: MIT License
Thank you for sharing your code.
You selected several better models and compare their performance. In the end, you only chose the best model for your final model. I don't know why you didn't ensemble your models to become a better final model. Possibly, this final model performs better than your the best single model.
When I used
python sklearn_randomforest.py --config_json_file=../../json/sklearn_randomforest.json --model_dir=$results_and_model_directory --dataset_dir=$path_to_dataset --process_num=$process --stage=0
to train random forest models, I got the following error message:
Traceback (most recent call last):
File "sklearn_randomforest.py", line 151, in
process_num = int(given_args.process_num)
ValueError: invalid literal for int() with base 10: ' '
I found given_args.process_num is a space ' ', so it can not be changed into an integer. Any advice? Many thanks.
I tried to run your test.ipynb. But I couldn't find '../../json/sklearn_randomforest_keck_pria_only.json' this file in you github. Would you like to provide it? Thanks
Now that our screening datasets are available on Zenodo, we could write a Python script that downloads the files to the dataset
subdirectory and creates the directory structure expected by the model training code.
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