Statistical analysis comparing six regression models (Multiple Linear Regression, Ridge, PLS, SVM, Random Forest, and Gradient Boosting) to predict pH levels in a beverage manufacturing process. Random Forest was selected as the final model based on validation performance (RMSE = 0.0995, R² = 0.649). The analysis identifies Manufacturing Flow Rate, Usage Rate, Bowl Setpoint, Filler Level, and Temperature as the top predictive factors. Created for regulatory compliance and process optimization.

African dwarf crocodile

Prueba

Reporte estadístico de la profundidad vertical con histogramas, ojivas y diagramas de caja realizado con RStudio.

Reporte estadístico de profundidad vertical con histogramas, ojivas y diagramas de caja realizado con RStudio.

MUHAVI prog