Video using JMP Pro 19 was posted in September 2026.

Predictive modeling involves selecting the right model, tuning it for the best performance, and scoring new data. Because no single algorithm works best for every problem, it’s important to screen, compare, and refine multiple models before selecting one for deployment. See how to implement a comprehensive predictive modeling workflow using JMP Pro by screening, refining, and comparing and then deploying your chosen model.

See how to:

• Automatically fit multiple predictive models
• Compare and contrast the performance of competing models
• Organize, profile and score models for deployment

This webinar covers: predictive modeling, machine learning, model screening, model comparison, Formula Depot  

Suggested Prerequisites:

• Familiarity with validation, test and training data

Resources

• Blog on using Shapely Values to quantify the contribution of each factor in your model down to the row level.
• Statistics Knowledge Portal information about hyperparameter tuning.
• JMP Marketplace extension for Neural Network Tuning for JMP Pro.