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# 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
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