{"data":{"full_name":"imehranasgari/ML-Classification-SVR-01","name":"ML-Classification-SVR-01","description":" This project explores the application of **Support Vector Regression (SVR)** using different kernel functions (linear, polynomial, and RBF) on synthetic and real-world datasets. The main objective is to **understand how various SVR kernels perform** in modeling complex, non-linear data, rather than just optimizing accuracy.","stars":0.0,"forks":0.0,"language":"Jupyter Notebook","license":"Apache-2.0","archived":0.0,"subcategory":"support-vector-machines","last_pushed_at":"2025-08-17T14:14:21+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":2.0,"adoption_score":0.0,"maturity_score":11.0,"community_score":0.0,"quality_score":13.0,"quality_tier":"experimental","risk_flags":"['stale_6m', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-13T00:12:23.949128+00:00"}}