newff Create a feed-forward backpropagation network. - Obsoleted in R2010b NNET 7.0.

I have this documentation... However since newff is obsoleted I was wondering how I can create the example feedforward neural network in the documentation with the new commands?

FEEDFORWARD NEURAL NETWORK
To create a feedforward backpropagation network we can use NEWFF 

   Syntax

   net = newff(PR,[S1 S2...SNl],{TF1 TF2...TFNl},BTF,BLF,PF) 
   Description

       NEWFF(PR,[S1 S2...SNl],{TF1 TF2...TFNl},BTF,BLF,PF) takes,
         PR  - Rx2 matrix of min and max values for R input elements.
         Si  - Size of ith layer, for Nl layers.
         TFi - Transfer function of ith layer, default = 'tansig'.
         BTF - Backprop network training function, default = 'trainlm'.
         BLF - Backprop weight/bias learning function, default = 'learngdm'.
         PF  - Performance function, default = 'mse'.
       and returns an N layer feed-forward backprop network.

Consider this set of data:
p=[-1 -1 2 2;0 5  0 5]
t =[-1 -1 1 1]
where p is input vector and t is target.

Suppose we want to create feed forward neural net with one hidden layer,  3 nodes in hidden layer, with tangent sigmoid as transfer function in hidden layer and linear function for output layer, and with gradient descent with momentum backpropagation training function, just simply use the following commands:

» net=newff([-1 2;0 5],[3 1],{'tansig' 'purelin'},’traingdm’);

Note that the first input [-1 2;0 5] is the minimum  and maximum values of vector p. We might use minmax(p) , especially for large data set, then the command becomes:

»net=newff(minmax(p),[3 1],{'tansig' 'purelin'},’traingdm’);

Answer 1

[Greg Heath]

There are two obsolete versions of newff. Using defaults for an I-H-O MLP,

net1 = newff(minmax(p),[ H O ]); %very obsolete

net2 = newff( p, t, H ); % obsolete

The latter version has the additional defaults of

 1. Removal of constant (zero variance) rows
 2. Mapminmax [-1,1] normalization of input and target 
 3. 70/15/15 train/val/test data division

It is not clear what versions of MATLAB and NNToolbox you have.

However, both obsolete versions should run. In addition, newfit and newpr are versions of the latter newff that are specialized for regression/curve-fitting and classification/pattern-recognition, respectively.

You can find the documentation for old and new functions in the MATLAB website. However, the commands help, doc, and type will yield most of the information you need to know for most functions on your machine.

Hope this helps.

Thank you for formally accepting my answer

Greg

[Ahmed Nasr]

I used "newff" command to train a net using input and output data each of size [300,3] for coordinate transformation successfully. How Can i use the trained network in predicting output of a new input dataset.

Thanks in advance.

[Greg Heath]

ynew= net(xnew);

Answer 2

[ben mus]

Hi, I'm a beginner in Matlab and I work in neural networks The question that poses is: How to know the number of imput layer and the number of hidden layer and the number of exit layer

net=newff(pr,[100 1],{'logsig' 'purelin'}, 'traingda', 'learngdm')

thank you.

[Greg Heath]

This is not an ANSWER.

Begin a new thread. However, before doing so, run the code in the documentation found at

 help newff
and
 doc newff

Other data for additional testing can be obtained from

 help nndatasets
and
 doc nndatasets

 You can find previous examples by searching both 
the NEWSGROUP and ANSWERS using

 help greg newff

Hope this helps

Greg

Answer 3

[raghad ali]

hello >> i'm trying to create a ANN ,but i've error net=newff(minmax(x),[10,1],{'tansig','pureline'} 'traingda', 'learngdm'); net=newff(minmax(x),[10,1],{'tansig','pureline'} 'traingda', 'learngdm');%% that's from matlab what this error .. how can i fixed please ?

[Greg Heath]

1. Correct spelling of purelin

2. Better yet, use as many defaults as possible by starting with the code in the help and doc documentation.

 help newff
 doc newff

Hope this helps.

Greg

Answer 4

[sehrish shah]

how we create feedforward network in MATLAB for the training for kdd data set using Gradient Descent algorithm?

Answer 5

[PIRC]

Simple example : AND Logic Gate DL netwok

https://in.mathworks.com/matlabcentral/fileexchange/78285-deep-learning-model-of-and-logic-gate