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Building Better Predictive Models Using JMP Pro - Model Screening

See how to screen models to find the most appropriate, best model for your needs and the goals of your study or experiment. Model Screening, introduced in JMP Pro 16,  streamlines your workflow to build and view results from multiple models at one time. The video does not cover building each type of model individually. 

 

 

See how to:

• Use validation options in Model Screening
• Use Decision Threshold for classification models
• Build Ensemble models to improve predictions
• Understand diabetes data used in today's examples
• Screen models for situations having a Continuous Response
• Use K-Fold Validation
• Deploy Decision Threshold for Binary Responses 

Resources

• Model Screening documentation, where it is useful, examples and reports 
• Decision Thresholds report for binary categorical variables
• How to use Ensemble Models

Predictive Modeling and Machine LearningRe: Building Better Predictive Models Using JMP Pro - Model Screening

Hello @andreacoombs1 

 

I would like to use the Model screening tool of the Analyze Prediticton  Modeling  to compare several ML methods with the XGBoost method simultaneously. Is that possible in the Model Screening platform or should I perform a severate analysis using a seperate cross validation folds for the XGBoost Method?

 

Regards,

 

Lu