Jmp 17 Pro -
0;1052;0;2cb; 0;d7;0;f1; 0;88;0;98; 0;279;0;17a; 0;1159;0;b19;
[Current Date]
: A new option that simplifies the tuning of machine learning models using a "Fast Flexible Filling" design. XGBoost Add-in jmp 17 pro
- Performance gains on large datasets (quicker redrawing and model fitting).
- More interpretable model outputs (enhanced variable importance, partial dependence).
- Broader statistical methods added or refined (notably GAMs and mixed-effects workflow).
- Stronger JSL editor and automation options.
- R-squared, adjusted R-squared
- RMSE, AICc, BIC
- Validation metrics (if using Holdback or K-fold)
- Significant factors (p < 0.05)
- Effect estimates
- Interaction plots
- Prediction profiler
: Integration for one of the most popular gradient boosting algorithms directly within JMP Pro. Wide Data Optimization Performance gains on large datasets (quicker redrawing and
JMP 17 Pro
is specifically designed for: