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| author | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-19 13:37:36 +0200 |
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| committer | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-19 13:37:36 +0200 |
| commit | d06f583dc59c6317e16370aa29b96bacaeaaa770 (patch) | |
| tree | ce7654a8e4ec784c8d53f7954d648dad1c04f83e | |
| parent | 6d4a2b0d9baef41ce26e5dd4639dd06dc99ea664 (diff) | |
Minor changes
| -rw-r--r-- | analysis/README.md | 14 | ||||
| -rw-r--r-- | simulations/README.md | 1 |
2 files changed, 14 insertions, 1 deletions
diff --git a/analysis/README.md b/analysis/README.md new file mode 100644 index 0000000..48e2e5e --- /dev/null +++ b/analysis/README.md @@ -0,0 +1,14 @@ +# Analysis + +## Files +- kmeans.R: Just here for doing some tests +- 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) +## Notes +Todo: remove minbucket=1 (does not impact the results) + diff --git a/simulations/README.md b/simulations/README.md index 1f7baad..70bb8b3 100644 --- a/simulations/README.md +++ b/simulations/README.md @@ -3,7 +3,6 @@ ## Folders - 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 ## Setup |