[1.2.2] Added sigma_fine parameter for independent control of neighborhood size during the fine training phase Configurable neighborhood function type (new parameter) Numba-JIT cosine similarity kernel for n_bmu=1 (performance improvement for metric="cosine") Optional X parameter in plot() for data-aligned PCA projections New example notebooks: manifold learning comparison, MiniSom comparison, metric comparison, RGB color map Parameter validation across all public methods with informative error messages Changed Refactored sigma parameter handling with improved default values Growth convergence logic switched to epoch-based control for more stable training Fixed sigma decay during coarse training phase to prevent premature convergence Improved predict_proba for hierarchical SOMs plot(): class labels are now mapped to strings when classes_ attribute is present Example-specific dependencies moved to optional examples dependency group Removed convergence_iter parameter — growth triggering logic has been simplified Fixed Numerical precision issues in weight updates Parameter validation now correctly triggered on fit() call Vertical growth winner indexing bug Sigma calculation bug Documentation Expanded and clarified runtime complexity analysis Added reference for the transform() method Fixed documentation URL (removed version-specific path) Full Changelog: https://github.com/SandroMartens/DBGSOM/compare/v1.2.0...v1.2.2