{"package":"r-metrica","ecosystem":"conda","exists":true,"latest_version":"2.1.1","repository":"","license":"MIT","description":"A compilation of more than 80 functions designed to quantitatively and visually evaluate prediction performance of regression (continuous variables) and classification (categorical variables) of point-forecast models (e.g. APSIM, DSSAT, DNDC, supervised Machine Learning). For regression, it includes functions to generate plots (scatter, tiles, density, & Bland-Altman plot), and to estimate error metrics (e.g. MBE, MAE, RMSE), error decomposition (e.g. lack of accuracy-precision), model efficienc","downloads_weekly":194,"deprecated":false,"health":{"score":59},"_cache":"db_only_bot","_partial":true,"_response_ms":1,"_powered_by":"depscope.dev — bot fast path (DB-only)","recommendation":{"action":"review"}}