This repository is an implementation of a Multi Layer Perceptron for the classification of alarms raised by the statistical model implemented by PokaPok association for the monitoring of the state of the ocean.
To set the environment for training and running the model, install the requirements using [environment.yaml]()
The repository is made of the following folders:
*[dataset_pandas](): Resulting datasets from feature engineering of the profiler's data
...
...
@@ -27,6 +27,7 @@ To **run** the model, the standalone script ``main.py`` is available. In the [ma
1.``--run single``: to run a single training of the model. This is useful to investigate the accuracy and loss evolution plots, as well as the confusion matrix for different setups.
2.``--run multiple``: to run the model for a fix model seed and different data splits. This is used to investigate the robustness of the model.
3.``--run generate_scores``: to generate the statistics about the data, that are stored in the logs and can then be plotted using the file bat_profile_plots.py
Two notebooks are provided to help gain information about the datasets: