How do I add R squared to control the Partition in the decision tree code?

[#1]

In the case of Boston housing.jmp, adjust the parameters of "Minimum Size Split" and "Split Best" in the JSL code to control the automatic Partition of decision tree.

Partition(
Y( :mvalue ),
X( :crim, :zn, :indus, :chas, :nox, :rooms, :age, :distance, :radial, :tax, :pt, :b, :lstat ),
Validation Portion( 0.3 ),
Minimum Size Split( 2 ),
Split Best( 1000 )
);

However, the R square of the validation group is <0 after the above code calculation.

Normally, in the decision tree model where verification group is performed on the Partition platform, the Partition will be automatically stopped before R square <0 of the verification group.

It looks like I'm going to add to my code to verify that the group R squared stops splitting, but I have no idea how to do that.I only found the manual.Thank you!

https://www.jmp.com/support/help/13-2/Example_of_a_Continuous_Response.shtml

……The solution found has four splits. The Split History plot shows that there is no further improvement in the validation data set after four splits. The RSquare value of 0.39 on the validation data does not support this model as a strong predictor of disease progression. The scatter across partitions in the partition plot further indicate that this model does not separate the Y levels well.……

[#2]

There is no editing function in posts, it should be "RSquare", I write "R squared", I hope you can understand, thank you!

[#3]

Consult a professional: how do I write code that makes JSL's results the same as the decision tree Partition results that are automatically executed on the platform?Thank you very much!