# define your experiment in main_sepsis.py
# e.g.
exp1 = Experiment(
experiment_id = cur_t + '_' + 'irl_greedy_physician_greedy',
policy_expert = em.pi_expert_phy_g,
save_file_name = cur_t + '_' + IRL_GREEDY_PHYSICIAN_Q_GREEDY ,
irl_use_stochastic_policy=False
)
em.set_experiment(exp1)
# run the following script in src/ directory
# e.g.
python main_sepsis.py -p -nt 5 -ni 15 -nb 2 -cm 'kp' -ns 100 -gnd
usage: main_sepsis.py [-h] [-gnd] [-v] [-up] [-cm {km,kp}] [-ns NUM_STATES]
[-p] [-nt NUM_TRIALS] [-ni NUM_ITERATIONS] [-nb {2,4}]
[-sp SVM_PENALTY] [-se SVM_EPSILON]
[-en EXPERIMENT_NAME] [-hm] [-net NUM_EXP_TRAJECTORIES]
process configuration vars
optional arguments:
-h, --help show this help message and exit
-gnd, --generate_new_data
-v, --verbose
-up, --use_pca
-cm {km,kp}, --clustering_method {km,kp}
kmeans or kprototype (cao, huang)
-ns NUM_STATES, --num_states NUM_STATES
-p, --parallelized
-nt NUM_TRIALS, --num_trials NUM_TRIALS
-ni NUM_ITERATIONS, --num_iterations NUM_ITERATIONS
-nb {2,4}, --num_bins {2,4}
-sp SVM_PENALTY, --svm_penalty SVM_PENALTY
-se SVM_EPSILON, --svm_epsilon SVM_EPSILON
-en EXPERIMENT_NAME, --experiment_name EXPERIMENT_NAME
name to be displayed in tensorboard
-hm, --hyperplane_margin
-net NUM_EXP_TRAJECTORIES, --num_expert_trajectories NUM_EXP_TRAJECTORIES
The module requires you have necessary data (Sepsis.csv) available in data/ directory.
- K prototype clustering