TL-iGeneCombo Paradigm

Paper Publication

[Pending]

Downloading data

Input datasets can be obtained through the README file in the GitHub repo.

Rerunning transfer learning experiments

Following SLTL installation, proceed to run the following command in Python:

SLTL.extract_SLTL_notebook(location = os.getcwd())

This will result in the TL-iGeneCombo notebook to appear in your working directory. The whole notebook can be ran to obtain TL results.

Running transfer learning experiments on new data

Following SLTL installation, proceed to run the following command in Python:

SLTL.extract_template_notebook(location = os.getcwd())

This will result in a template notebook to appear in your working directory. This notebook can be modified to allow TL applications on new datasets.

Furthermore, both notebooks can be converted into python scripts to allow for CLI access by using the following command:

jupyter nbconvert --to script *.ipynb

Then, each Python file can run like the following:

# run once to obtain the results
python SLTL_notebook.py --seed=1 --re_evaluate=0 --re_save=0

# run again with re_evaluate being on for ensemble results
python SLTL_notebook.py --seed=1 --re_evaluate=1 --re_save=0