How to predict through artificial neural networks

Tansu
Tansu New Altair Community Member
edited November 5 in Community Q&A
Dear friends
I am trying to make predictions using artificial intelligence networks.
My data set is below.(it goes all the way down to 4500 rows, I picked some of them)

Tarih ptf (market price)  PTFS PTFG PTFH1 PTFH2 PTFH3 PTFH4 PTFH5 HVSC
1/01/2012 00/00 149,99 130,00 150,99 149,99 139,96 149,99 149,99 145,00 6,50
1/01/2012 01/00 129,99 149,99 138,99 138,01 130,00 130,93 146,79 145,00 6,00
1/01/2012 02/00 117,14 129,99 129,94 129,74 110,01 129,92 145,00 143,00 6,00
1/01/2012 03/00 101,72 117,14 128,99 117,00 35,04 110,06 139,93 135,00 7,00
1/01/2012 04/00 53,99 101,72 116,99 104,81 20,17 99,98 130,01 129,00 6,50
1/01/2012 05/00 53,99 53,99 116,99 104,54 45,48 100,00 130,93 135,00 6,00
1/01/2012 06/00 55 53,99 119,93 100,00 110,00 99,97 129,56 110,00 6,00
1/01/2012 07/00 35,05 55,00 115,68 58,91 53,00 52,99 124,95 105,00 6,50

Here is the path I followed:
Read excel/normalize/set role (ptf ( market price) is my dependent variable and labelled)/multiply/filter example (training)/filter example (test)/neural test/apply model/performance regression

When I follow this path, 6 sigmoid and 1 linear regression nodes appear.
As a result, I get the predicted values of the already known market price.
My question is, how do I get the predictive value of market price without knowing and taking the market price as the dependent variable?
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