SmartKNN v0.2.3 Released

SmartKNN v0.2.3 Released - Stability, Performance, and Global Distance Improvements I’m excited to share the release of SmartKNN v0.2.3 , the latest update to the SmartKNN library. This version focuses on improving stability, deterministic behavior, and performance , while also introducing a new feature that helps the model capture broader structure within datasets. SmartKNN is designed as a modern approach to the classic K-Nearest Neighbors algorithm. The goal is to make KNN more practical for real-world tabular machine learning , with better scalability, learned feature weighting, and optimized CPU inference. What’s New in v0.2.3 One of the key additions in this release is global structure distance integration . In addition to the standard feature-level distance used by traditional KNN, SmartKNN now supports an optional parameter called global_lambda . This allows the model to incorporate dataset-level structure when ranking neighbors. In many datasets this small structural awareness