v0.1.0

[0.1.0] - Initial Release

📁 Project Structure

• Added essential project files: CODE_OF_CONDUCT.md, MANIFEST.in, LICENSE, CITATION.cff, and requirements.txt
• Added structured layout for examples/, tests/, and docs/ (documentation site)

🧰 Helpers Module

• Added helpers package:
  • verifier: input and parameter validation
  • evaluator: evaluation metrics
  • data_scaler: feature normalization
  • data_preparer: dataset scaling and splitting
  • callbacks: custom callback functionality
  • wavelet_funcs: wavelet function definitions and management
  • wavelet_layers: PyTorch-based wavelet layer implementations

🧠 Models Package

• Added models package:
  • base_model.py: defines BaseModel for consistent design and logic reuse
  • custom_wnn: custom wavelet neural network implementations (4 types)
  • gd_wnn: fully gradient-descent-based WNNs:
    • GdWnnClassifier: for classification tasks
    • GdWnnRegressor: for regression tasks
  • mha_wnn: fully metaheuristic-optimized WNNs:
    • MhaWnnClassifier: for classification
    • MhaWnnRegressor: for regression