Welcome! This is the git repository of the paper "A Critical Review of Multi-Output Support Vector Regression".
To run the workflow on a local machine, please do the following:
First, install Snakemake if you haven't already. (The version we used is 7.8.5.)
Then, you can set the configurations like the files to process, solvers to use, hyperparameters, etc. in config.yaml.
After done configurating, you can either run
snakemake -s Snakefile_bt --use-conda --cores <number of cores or 'all' (without quotation marks)> for bootstrapping or
snakemake -s Snakefile_cv --use-conda --cores <number of cores or 'all' (without quotation marks)> for nested cross-validation.
(If the command snakemake is not recognized, you may need to activate your snakemake environment with conda activate snakemake.)
To run the workflow on a cluster, please do the following:
Change cluster/jobscript.sh and env_cluster.yaml according to your cluster.
Then, you can set the configurations like the files to process, solvers to use, hyperparameters, etc. in config.yaml.
After done configurating, you can run
sh execute_on_cluster.sh -p project_ID -j max_nr_of_concurrent_jobs -r {bt | cv} [-R rule_to_rerun] [-u rule_to_stop_at] [-n (for a dry run)].