* wip: add function to create stratified train-test split from STFT data
* feat(src): implement working function for dataset B to create ready data from STFT files stft_files and add setup.py for package configuration
* feat(notebook): Update variable names for clarity, remove unused imports, and streamline data processing. Implement data concatenation using pandas concat for efficiency. Add validation steps for Dataset B and improve model training consistency across sensors.
* fix(.gitignore): add rule to ignore egg-info directories and ensure proper formatting
* docs(README): add instructions for running stft.ipynb notebook
* feat(notebook): Add evaluation metrics and confusion matrix visualizations for model predictions on Dataset B. Remove commented-out code and integrate data preparation using create_ready_data function.
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Co-authored-by: nuluh <dam.ar@outlook.com>
- Create a Python script to generate CSV files in a structured folder hierarchy under `data/processed` with specific damage levels and tests.
- Add a `.gitignore` file to exclude CSV files from Git tracking, enhancing data privacy and reducing repository size.
- Include a `README.md` in the `data` directory to clearly document the directory structure, file content, and their intended use for clarity and better usability.
Closes#7
