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vivianclmnz
Calcite | Level 5

a network has been trained using the below statements (if it is correct!)

proc neural data=vivian.hyper dmdbcat=vivian.hyper1 graph;

arch mlp hidden=3;

input x y z/ level=interval id=i;

target acceptability / level=interval id=o;

train out=vivian.outn outest=vivian.outw outfit=vivian.outf;

save network=vivian.hypert;

run;

how do one make use of the trained network above to form a new network, where if one just adds the value of the inputs x y z, will be able to get the target 'val' (being a binary value '1' or '2' / 'yes' or 'no') automatically? (plz correct if the above trained network is wrong)e of

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vivianclmnz
Calcite | Level 5

data trito;

input x y z;

datalines;

200 2 0

;

run;

proc neural data=vivian.hyper dmdbcat=vivian.hyper1 network=vivian.hyper1 graph;

input x y z / level=interval id=i;

target z/ level=interval id=o;

train;

score data= trito out=outf role=score;

run;

this is how a trained network can be made use of, using score statement. if someone feel it is wrong plz correct.

also plz clear on how to work on the value of objective function if anybody is aware of, thank you.

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