v0.8.0

Geochemistry π v0.8.0

✨ New Features

• Multi-output Regression: Predict multiple continuous target variables simultaneously (multiple X → multiple Y) with FLAML AutoML integration
• Multi-output Classification (Experimental): Predict multiple class labels simultaneously with XGBoost native multi-strategy support
• OPTICS Clustering: Density-based clustering without pre-specifying the eps parameter
• Automated Clustering Evaluation: One-click Silhouette score calculation and visualization for K=2 to K=10
• Time Series Analysis: Independent module with customizable bin width, bootstrap iterations, and uncertainty quantification
• New Built-in Dataset: Data_Time_Series.xlsx for time series analysis demonstration

🔧 Improvements

• Feature selection automatically skipped for multi-output tasks
• MLflow parameter logging optimized for multi-output hyperparameters
• Visualization functions now support multi-output (each target gets separate plots)
• README enhanced with badges, structured tables, and Star History chart

🐛 Bug Fixes

• Fixed fit() call in MultiOutputRegressor and MultiOutputClassifier
• Fixed MLflow parameter length limit (500 chars) by splitting long hyperparameters
• Fixed LightGBM compatibility issues in multi-output tasks
• Fixed Python 3.9 type annotation compatibility (dict | None → Optional[dict])
• Fixed silhouette_score import in clustering module
• Resolved application data null value problem (PR #426)
• Fixed SVM and Decision Tree AutoML runtime issues (PR #429)