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| author | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-19 13:36:32 +0200 |
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| committer | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-19 13:36:32 +0200 |
| commit | 6d4a2b0d9baef41ce26e5dd4639dd06dc99ea664 (patch) | |
| tree | 9fcddfbb728e347905180e1745a2e7a329ea8965 /README.md | |
| parent | 4f1b2ea492d3e19c81ab98f050618d437b6e9ec5 (diff) | |
Update READMES
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 27 |
1 files changed, 9 insertions, 18 deletions
@@ -1,20 +1,11 @@ # 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 +## Folders + +- `analysis/` + - Contains data analysis + offline and in-situ training code. + - More info in `analysis/README.md`. +- `simulation/` + - Contains the simulator source code and script to run the experiments from the paper. +- `slides_recap/` + - Just backup slides. Nothing interresting. |
