Hello community,
I am testing several models as part of JSL loop in JMP 16, using different validation columns to determine how the R2 values change depending on what data is used. Each validation column contains a subset of the data, with some missing data at the beginning and/or the end of the column.
Other models, such as the Bootstrap, run well simply ignoring missing values but the Neural Net keeps throwing an error message (reproduced on the JMP sample data set, CrimeData).
I can work around the problem by including a filter column, setting all missing values to 0 and not running them. But this will require a filter column for each validation column (or dynamical creating/deleting a column each iteration).
Neural(
Y( :Murder Rate ),
X(
:Robbery Rate, :"Agg-Aslt Rate"n, :Burglary Rate, :Larceny Rate,
:MVTheft Rate
),
Validation( :Validation ),
Informative Missing( 0 ),
Fit( NTanH( 3 ) ),
Where( :Filter == 1 )
)
Has anyone else encountered this issue and found a solution? Thanks!
