I am new to JMP and after completing the online Statistical Thinking for Industrial Problem Solving course, I have a few questions. How do I save a particular optimized model of say a Bootstrap Forest (after determining it has a desirable R-squared and MSE) and then apply it to predict results on a new test data? How do I see the newly predicted results? This is the whole essence of predictive modelling. Is it possible to see the residual plot of my selected Bootstrap Forest model? The course only presented how to evaluate a model's performance, without showing how to apply the models for future predictions.
Thank you.
You probably want to ask this over on the JMP forum.
@pcofoche wrote:
I am new to JMP and after completing the online Statistical Thinking for Industrial Problem Solving course, I have a few questions. How do I save a particular optimized model of say a Bootstrap Forest (after determining it has a desirable R-squared and MSE) and then apply it to predict results on a new test data? How do I see the newly predicted results? This is the whole essence of predictive modelling. Is it possible to see the residual plot of my selected Bootstrap Forest model? The course only presented how to evaluate a model's performance, without showing how to apply the models for future predictions.
Thank you.
You probably want to ask this over on the JMP forum.
@pcofoche wrote:
I am new to JMP and after completing the online Statistical Thinking for Industrial Problem Solving course, I have a few questions. How do I save a particular optimized model of say a Bootstrap Forest (after determining it has a desirable R-squared and MSE) and then apply it to predict results on a new test data? How do I see the newly predicted results? This is the whole essence of predictive modelling. Is it possible to see the residual plot of my selected Bootstrap Forest model? The course only presented how to evaluate a model's performance, without showing how to apply the models for future predictions.
Thank you.
My question got resolved at the JMP forum. Thank you.
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