Hybrid Autoencoders for Tabular Data - Supplementary Code

Requirements:
- Python 3.8 or higher
- Install required packages from requirements.txt

Usage:
1. Extract dataset:
   - Edit extract_openml_dataset.py with the desired OpenML dataset ID and parameters.
   - Run: python extract_openml_dataset.py
   - This creates preprocessed CSV files in openml_datasets/<dataset>/

2. Train and evaluate model:
   - Edit main.py to select your dataset and model type (default is TANDEM).
   - Run: python main.py
   - Final evaluation metrics will be printed.

3. Spectral analysis (optional):
   - Edit plots_and_visualizations/spectral_analysis.py to set dataset/model paths.
   - Run: python plots_and_visualizations/spectral_analysis.py
   - Output plots will be saved in the spectral_analysis_plots/ directory.