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Is there any downside of pruning your neural network?
Nets with one hidden layer can be universal approximators. From 1979 to 2003 I used FORTRAN to design 2 class classifiers. T...

10 years ago | 1

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how we can have multiple targets in neural network training
Construct one target matrix with four dimensional columns. If you have ten inputs construct one input matrix with ten dimensiona...

10 years ago | 1

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How to train a feedfordward neural network with error weights
Use the command window help mse doc mse Hope this helps. *Thank you for formally accepting my answer* Greg

10 years ago | 0

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Answered
RNG neural Network and outputs
I typically 1. Initialize rng once and only once before training (henever you use the rng it AUTOMATICALLY moves to anothe...

10 years ago | 0

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Neural Network keep best weight and how to use without training
You probably have to transpose weight. Type whos weight and reread the help and doc documentation to make sure the dimen...

10 years ago | 0

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How to get target data for neural networking toolbox?
Use class indices 1:4 for the classes speedbumps, potholes, roughness and goodroad. Then use the ind2vec function to ob...

10 years ago | 0

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How can I get predicted values from an open-loop Narxnet following other predicted values? Or is just possible with closed loop?
Using the openloop configuration requires a target input. When you run out of target data you have to use the closeloop configur...

10 years ago | 0

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Answered
does anybody ever use neural network to do a prediction with regularization optimization instead of early stopping?
% Thank you so much, Greg. I should have posted my question earlier, it really helps a lot! %I did not run several multiple t...

10 years ago | 0

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Problematic Ordinal Input Categorical Output Neural Network
1. It looks like you can delete the above equations because they are defaults. 2. You definitely need to substantially reduce...

10 years ago | 0

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Answered
How can I solve this equation a*x^2+b*x+c=0 with neural network (toolbox)
Neural networks learn fixed weights from multiple input/output examples. [ 0, b c ] => [ -b/c ; NaN ] [ a; b; c ] =...

10 years ago | 0

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Manually reproduce results from a neural network generated from Matlab
Type "whos" to see the dimensionality of all variables and parameters. % help newpr % doc newpr % Obsoleted in R2010b NN...

10 years ago | 0

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Answered
does anybody ever use neural network to do a prediction with regularization optimization instead of early stopping?
GEH1=' Predictions are performed with timeseries functions' GEH2=['You are using FITNET which is used for REGRESSION and CURV...

10 years ago | 0

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Answered
does anybody ever use neural network to do a prediction with regularization optimization instead of early stopping?
Compare your own code with numerical results from a. A modification of the simpler code in the documentation help fit...

10 years ago | 0

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Using PNN neural network method or by using RBF radial basis function, what would be the spread value? Which one will provide best result PNN or RBF
Try looking at some of my NEWRB posts in BOTH the NEWSGROUP and ANSWERS. newrb greg Probably looking at the most recent o...

10 years ago | 0

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Answered
How to use MATLAB's neural network tool box for minibatch gradient descent?
True to his word, Dr. Heath has posted http://www.mathworks.com/matlabcentral/newsreader/view_thread/344511#943659 Hope t...

10 years ago | 0

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How can I predict future output based on input data using neural network?
y =net(x); Hope this helps, *Thank you for formally accepting my answer* Greg

10 years ago | 0

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Correlation of input variables in ANN
Matlab can handle highly correlated inputs. However, if you want to interpret the output in terms of the inputs, you can recursi...

10 years ago | 1

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Answered
How to use MATLAB's neural network tool box for minibatch gradient descent?
There is no problem; Train in a loop. However, do not configure or initialize the net between the minibatches of training data....

10 years ago | 1

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Non-linear parameter estimation (least squares)
Always begin searches with the lookfor command. Follow up with help and doc >> lookfor 'least square' lscov - Least square...

10 years ago | 0

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Answered
How to forecast next 20 points with NARX neural net?
0. I ran your code with the RNG initialization statement rng('default') just before the training command. The results we...

10 years ago | 0

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DESIGNING AN ELMAN NET PROJECT
See above

10 years ago | 0

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how to create large dataset to train neural network for software fault prediction?
For N O-dimensional output targets corresponding to N I-dimensional inputs [ I N ] = size(input) [ O N ] = size(target) ...

10 years ago | 0

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NARXNET with input delay
No. TIMEDELAYNET is used to predict an output series, y, using an exogeneous external input series x. NARXNET is used to ...

10 years ago | 0

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Neural Network result offset by one
1. Since I always use a. t and y to denote target and output b. subscripts "o" and "c" to denote "o"penloop ...

10 years ago | 0

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The best Ann configuration
Insuffient information and explanation: size(input) ? size(target) ? If I guess both are [ 1 N ] , Ntrn ~ 0.7*N and Hub ...

10 years ago | 1

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Neural Network Input Size and Data Issue - HELP
You are making this harder than it is. For the 1st time through all you have to specify is 1. Type of network a fitnet fo...

10 years ago | 0

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problem with feed-forward backpropogation
size(data ) = [ 1 1500 ] input = data(1:end-3); target = data(4 : end); Hope this helps *Thank you for formally acc...

10 years ago | 0

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which type of input to be given to the neural network
For N I-dimensional Inputs yielding N O-dimensional Outputs [ I N ] = size(input) [ O N ] = size(target) Hope this help...

10 years ago | 0

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How can I train multiple sequences in neural network using feedforwardnet?
close all, clear all, clc [ X0 T0 ] = simplenarx_dataset; X(1,:) = X0(1:end-2); X(2,:) = X0(2:end-1); X(3,:) = T0(1:end-2...

10 years ago | 2

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Answered
how can I give input to the neural network in the matrix form?
For N I-dimensional input / O-dimensional target pairs [ I N ] = size(input) [ O N ] = size(target) Hope this helps ...

10 years ago | 0