my idea is to create a net on one testing case. than i want to train this net with my other testing resaults????
neural network??
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Markus
el 14 de Jun. de 2012
Editada: Greg Heath
el 9 de Ag. de 2015
hi Guys! i have no experience with the neuronal toolbox. But i hope that i can solve these problem: My problem sounds not so difficult:
i have different testing resaults. - 1 channel: enginge speed - 2 channel: preassure - 3 channel: temperature trend of the cooling medium
my unknown signal is an other temperature trend. First of all i installed a temperature-senor on the place to get the unknown signal to study the behavior of heating. I tried 7 testing with different load cases. now i have 7 different behaviors of the temperatur trends dependent on the 3 channels.
by the way, in the future i have to deinstall the sensor..... is it possible to solve this problem with the neural network toolbox? i want to create a kind of forecast of the temperature-trend with the help of the testing resaults.
who can help???
Respuesta aceptada
Greg Heath
el 23 de Jun. de 2012
The construction of the net is basic. See the documentation, examples and demos.
The basic problem is that with N = 7 you probably do not have enough training data for an accurate I-H-O = 3-H-1 network. If you use all the defaults of FITNET or NEWFF, H = 10, Ntrn ~ 0.7*N = 5, Nval = 1 and Ntst = 1.
The number of unknown weights is Nw = (I+1)*H+(H+1)*O = 40+11 = 51
However, the number of training equations is only Neq = Ntrn*O = 5 << Nw
Possible solutions which can be combined:
1. Obtain more data.
2. Decrease H
3. Regularized training with TRAINBR
4. Simulate new data by adding noise to the current inputs (but not to outputs)
5. Average the outputs of multiple nets selected from
a. Many different weight initializations and data divisions.
6. I suggest you begin with
a. Standardize all variables to zero-mean/unit-variance
b. Calculate the 4-variable correlation coefficient matrix
c. Plot the 3 outputs vs the input
d. Ponder the results of c and d
e. Vary H with Ntrials(=20) weight-initializations for each
candidate value of H.
Hope this helps.
Greg
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omar belhaj
el 7 de Jul. de 2014
Editada: omar belhaj
el 18 de Jul. de 2014
Ntrn ~ 0.7*N
what's mean Ntrn (number of training= number of epochs)!!!!???
and why 0.7 ????
what's diffrent between FITNET and NEWFF???
Vary H with Ntrials
what's mean Ntrails ???? it is number of trials ie number of epochs???
best regards
thank you very much Greg
Más respuestas (6)
Greg Heath
el 26 de Jun. de 2012
Training has to be done with a subset that has the dominant characteristics of all the data. One case is not sufficient. If training to convergence without a validation set you should require Neq >= Nw but desire Neq >> Nw. Otherwise the net is too sensitive to measurement errors and noise resulting in poor performance on nontraining data.
Ponder the results of b and c so that you are somewhat familiar with the relationships between the variables.
If you use Nval = Ntst = 1, there are 7*6 = 42 possible data divisions. For each singleton test set, there are 6 possible singleton validation sets.
For each data division you can try numH (=10?) values for the number of hidden nodes, H.
For each value of H you can design Ntrials (=10?) nets with different random initial conditions.
Since this is a very small data set it shouldn't take long to run 10s of trials. Just be sure that you remember the initial random number seed and keep track of how many random number calls are made before each design is made.
It is not unusual for me to design with a single, but much larger data set, 10 random weight initialization trials for each of 10 different values for H. Search the Newsgroup with
heath close clear newff Ntrials
Hope this helps.
Greg
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Markus
el 2 de Jul. de 2012
1 comentario
Greg Heath
el 3 de Jul. de 2012
There are a plethora of demos and examples in the documentation, the code is similar for all dimensions.
If you have problems, include code and error messages with your post.
Greg
Greg Heath
el 3 de Jul. de 2012
>it works very well for these data "102". but now i want to know how i can adapt this net to other datas?
>u have an idea? is it possible to contact u in >ICQ oder something else?
Very simple:
Depending on version
newoutput = sim(net,newinput); or newoutput = net(newinput);
Hope this helps.
Greg
0 comentarios
Markus
el 4 de Jul. de 2012
3 comentarios
Greg Heath
el 19 de Jul. de 2014
Editada: Greg Heath
el 9 de Ag. de 2015
> Ntrn ~ 0.7*N >> what's mean Ntrn (number of training= number of epochs)!!!!??? >> and why 0.7 ????
The default data division is [Ntrn,Nval,Ntst]= [0.7,0.15,0.15]*N
>what's diffrent between FITNET and NEWFF???
Compare the results of
help newff % obsolete
help fitnet % current
and
doc newff
doc fitnet
Basically
newff is obsolete. It takes (x,t,H) as inputs and automatically assigns initial weights
- newfit(obsolete) is a special case for regression and curvefitting. It calls newff
- newpr(obsolete) is a special case for classification and pattern-recognition. It also calls newff
feedforwardnet is current. it takes (H) as input and does not assign initial weights. Weights can be assigned at any time by configure(net,x,t). However, train(net,x,t) will automatically assign initial weights to weightless nets before training.
-fitnet(current) is a special case for regression and curvefitting. It calls feedforwardnet.
-patternnet(current) is a special case for classification and pattern-recognition it also calls feedforwardnet
>>Vary H with Ntrials
>what's mean Ntrails ???? it is number of trials ie number of epochs???
The best value for H is, typically, not known AND random initial weights may not result in a good design. Therefore I design Ntrials = 10 designs for each value of H that I try.
If [I N ] = size(x) and [I O ] = size(t), the number of default training
equations is Ntrneq = Ntrn*O ~0.7*N*O and the number of unknown weights is Nw = (I+1)*H+(H+1)*O = O+(I+O+1)*H. If Nw >~ 0.5*Ntrneq you should use a validation set or use trainbr.
Before you ask about functions, check with the help and doc commands.
AND, if you need additional examples, search NEWSGROUP and ANSWERS using greg as an additional search word. For example
greg newff
greg fitnet
greg Ntrials
Hope this helps.
Greg
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