# loosely-policies-analytics

## Analysis folder
- offline.R: contains two major functions:
  - build_models: To generate K-fold cross-validation results (note that hyper-parameters for decisions tree is fixed (no validation set))
  - generate_inputs: generate the inputs for the simulations experiments + the decision tree plots
- in-situ.R: Implement the in-situ learning approach (Figure 4a 4b and 4c)
    - For figure 4a and 4b we train the model with increasing amount of data from previous results as if we were using one policy per day (see section IV.A)
    - For figure 4c, delta is generated by comparing using each policies in round-robin (one per days to perform the training)
        to each previous paper results with single policy only (see paper section IV.A)

Todo: remove minbucket=1 (does not impact the results)

## Simulation folder

- src/: contains the simulator code (based on SimGrid)
- libs/: contains a setup script that will fetch and configure the correct SimGrid version
    - see simulation/README.md for more info
- results/: Contains all needed script to run the experiments
    - In particular paper.sh generates the results present in the paper