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+# 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)
+