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Dec 8, 2009 2:20 PM
(384 views)

X1, X2, X3, X4 are input

Y is output:

H1:intercept

H1:X1

H1:X2

H1:X3

H1:X4

H2:intercept

H2:X1

H2:X2

H2:X3

H2:X4

My first question: when I calculate the H1 as H1=1/(1+exp(-(intercept + Sum(H1:Xi*Xi)) is not the H1 value JMP provided.

My second question; I assume the H1 and H2 values from JMP calculation are correct and using the linear combination of them get the correct value YHat1.

However, how to use the YHat1 to calculate the Y. JMP's guide said: there is a

S_y(X) function as "The Identity function". From math, I assume it is just one since I only test one Output Y. The result I can not get right comparing with JMP prediced value.

I feel that part of Guide is too brief without many math definition and seem to me there is no easy way to implement the Neural model to predict without writing JSL.

I do want to write an independent scripts (out of JMP) to predict.

Appreciat someone can offer any help! Thanks in Advance! Ming

3 REPLIES

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Dec 8, 2009 5:34 PM
(299 views)

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Dec 9, 2009 7:38 AM
(299 views)

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Dec 9, 2009 8:55 AM
(299 views)

also, can you explain why the RSquare Cross Validation (CV R2) can be negative?

I got trainind set R2 = 0.9 and CV R2 = -3.2 and R2 (both training and cross validation) is 0.95. That does not make sense to me!