Commit 3b78e6da authored by José Hugo Elsas's avatar José Hugo Elsas
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First draft of the README.md file.

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Accessory repository for the paper "Active Learning Loading Case Selection" including notebooks and data necessary to reproduce all results of the paper.
# Included Files :
The files in this repository correspond either to Notebooks, containing the code used to produce the results, or data files.
## Notebooks
- Spreadsheet aggregation.ipynb
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- Single-Target random and active learning for loading case selection.ipynb
As an example
As the base example from the active learning method, the information-based objective function is the uncertainty of a single inferred variable. For each of the variables of interest, the active learning procedure is performed sampling over a single variable, therefore it serves as the best case scenario since the samples are the best possible to maximize the information coming from that one variable.
It also serves as benchmark for the multi-target case since, if the later takes much longer than the single variable selection, it could provide an indication that the problem of jointly sampling multiple target variables constitutes a much more difficult problem than the one of sampling a single variable.
- Multi-Target random and active
- Multi-Target random and active learning for loading case selection.ipynb
The main notebook for the work. It provides an implementation of the active learning method, using as information-based objective function the geometric mean of the uncertainty of all variables of interest.
## Data Files
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