Project name: A meta-learning approach for genomic survival analysis
Project home page: https://github.com/gevaertlab/metalearning_survival.
Operating system(s): Platform independent
Programming language: Python
Other requirements: Python 3.6.6 or higher, Pytorch 0.4.1
License: BSD 3-Clause License
Example usage
Direct learning
python direct_learning_subsettarget.py --config 'example_config/direct_learning_train_config.json'
python direct_learning_eval.py --config 'example_config/direct_learning_eval_config.json'
Combined learning
python combined_learning.py --config 'example_config/combined_learning_train_config.json'
python neuralnet_eval.py --config 'example_config/combined_eval_config.json'
Regular pre-train fine-tune
python pretrain_coxnet.py --config 'example_config/pretrain_coxnet_config.json'
python finetune.py --config 'example_config/fintune_config.json'
python neuralnet_eval.py --config 'example_config/finetune_eval_config.json'
few-shot meta-learning
python fewshot_metatrain.py --config 'example_config/fewshot_meta_config.json'
python fewshot_finaltrain_eval.py --config 'example_config/fewshot_finaltrain_config.json'