Permutation Tests and Monte Carlo Cross Validations Using the Simulation Platform

[#1]

I'm trying to do permutation tests and Monte Carlo Cross Validations with the Iris sample dataset as a MWE for our dataset. I'm not sure if I'm doing things and interpreting output correctly.

1) Create New Formula Column (Random->Sample Without Replacement) for the Species Column for Permutation Test.

2) Create a Validation Column (0.75/0.25 split) and a new Formula Column (Random->Sample Without Replacement) using this for Monte Carlo Cross Validation

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3) Run the Discriminant Platform with the Validation column and display the ROC curves. Use the Simulate Platform on the Area of the ROC Curve

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4.1) For the Permutation Test-Select Species as column to switch out and Shuffle[Species] as column to Switch In. Enter the desired number of random sampling and random seed and run the simulation. 

mjmg_1-1638372281372.png

4.2) View the Distributions script and take note of the empirical p-value.

mjmg_2-1638372528310.png

5.1) For the Monte Carlo Cross Validation-Select Validation as column to switch out and Shuffle[Validation] as column to Switch In. Enter the desired number of random sampling and random seed and run the simulation.

mjmg_4-1638372900805.png

5.2) View the Distributions script and take note of the empirical p-value.

mjmg_5-1638373060746.png

6) Assuming what I did is correct (testing the Area of ROC curve), the low p-value from the Permutation test is expected, but what about the large p-value for the Monte Carlo cross validation? How should this be interpreted?

Thanks