Answered

cross validation in neural network using K-fold

%i am using neural network for classification but i need to use instead of holdout option , K-fold. ==> FALSE!. You mean y...

cross validation in neural network using K-fold

%i am using neural network for classification but i need to use instead of holdout option , K-fold. ==> FALSE!. You mean y...

12 månader ago | 0

Answered

Can the number of Predictors be different for Train and Test data?

Of course not. The ultimate purpose of training is to create a model that works well on non-training data. Thank you for form...

Can the number of Predictors be different for Train and Test data?

Of course not. The ultimate purpose of training is to create a model that works well on non-training data. Thank you for form...

12 månader ago | 0

Answered

How to check the robustness of the Neural network model?

If you are going to test with white noise, include white noise in your design (i.e., training + validation) Then, given a fixed...

How to check the robustness of the Neural network model?

If you are going to test with white noise, include white noise in your design (i.e., training + validation) Then, given a fixed...

12 månader ago | 0

| accepted

Answered

NARX with Complex Values Input

Decades ago I learned (the hard way) to forget about trying to use complex computations for NNs. However, if you insist, let us...

NARX with Complex Values Input

Decades ago I learned (the hard way) to forget about trying to use complex computations for NNs. However, if you insist, let us...

ungefär ett år ago | 1

Answered

Why sets Matlab automatically the activation functions for a neural network like this?

That is a standard configuation for a neural net. It's operation is explained in every elementary text. Thank you for formally...

Why sets Matlab automatically the activation functions for a neural network like this?

That is a standard configuation for a neural net. It's operation is explained in every elementary text. Thank you for formally...

ungefär ett år ago | 0

Answered

How to plot Network performance?

You have lost training information, So the only thing left is output vs input. Hope this helps. Thank you for formally ac...

How to plot Network performance?

You have lost training information, So the only thing left is output vs input. Hope this helps. Thank you for formally ac...

ungefär ett år ago | 0

Answered

Elman Neural Network (ENN)

size(P_TRAIN) = [ 1296 1728] size(T_TRAIN) = [ 432 1728] Hope this helps. *Thank you for formally accepting my answer* ...

Elman Neural Network (ENN)

size(P_TRAIN) = [ 1296 1728] size(T_TRAIN) = [ 432 1728] Hope this helps. *Thank you for formally accepting my answer* ...

ungefär ett år ago | 0

Answered

NARX re-training in closed loop

Using 100 feedback delays makes no sense. Only use feedback delays that are within the correlation length of the function. See...

NARX re-training in closed loop

Using 100 feedback delays makes no sense. Only use feedback delays that are within the correlation length of the function. See...

ungefär ett år ago | 1

Answered

Can CNN train separately instead of learning everything at one time?

I try to have the order of inputs as random and uncorrelated as possible. Otherwise the probability of extensive learning/unlear...

Can CNN train separately instead of learning everything at one time?

I try to have the order of inputs as random and uncorrelated as possible. Otherwise the probability of extensive learning/unlear...

ungefär ett år ago | 0

Answered

In evaluating a neural net, should NMSE be based only on test subset of data?

For serious work I calulate FOUR values of NMSE: 1.70% Training 2.15% Validation 3.15% Test 4.100% All for 10 (typically...

In evaluating a neural net, should NMSE be based only on test subset of data?

For serious work I calulate FOUR values of NMSE: 1.70% Training 2.15% Validation 3.15% Test 4.100% All for 10 (typically...

ungefär ett år ago | 0

| accepted

Answered

Is the "patternnet" a fully connected neural network

Yes. The only difference between my classifiers and regressors is the sigmoid output layer instead of linear. Hope this helps....

Is the "patternnet" a fully connected neural network

Yes. The only difference between my classifiers and regressors is the sigmoid output layer instead of linear. Hope this helps....

ungefär ett år ago | 0

| accepted

Answered

How to train and test time series data in Neural Network Toolbox

I order to test a net you have to compare the actual output with the desired output. Hope this helps. THANK YOU FOR FORMALLY...

How to train and test time series data in Neural Network Toolbox

I order to test a net you have to compare the actual output with the desired output. Hope this helps. THANK YOU FOR FORMALLY...

ungefär ett år ago | 0

Answered

Artificial Neural Network implementation and to know the importance of each of the input on output(Response) - wanted help

The way I determine the importance of a single input is 1. Calculate the error using all inputs 2. Loop over inputs ...

Artificial Neural Network implementation and to know the importance of each of the input on output(Response) - wanted help

The way I determine the importance of a single input is 1. Calculate the error using all inputs 2. Loop over inputs ...

ungefär ett år ago | 0

| accepted

Answered

transfer function purelin equation based on neural network toolbox

Read the documentation help purelin doc purelin Greg

transfer function purelin equation based on neural network toolbox

Read the documentation help purelin doc purelin Greg

ungefär ett år ago | 0

Answered

How to use a sequenceInputLayer with a regressionLayer (neural networks) ?

The answer is obvious: help regressionlayer doc regressionlayer *Thank you for formally accep...

How to use a sequenceInputLayer with a regressionLayer (neural networks) ?

The answer is obvious: help regressionlayer doc regressionlayer *Thank you for formally accep...

mer än ett år ago | 0

Answered

Time Domain Signal for neural network

If you have rpm I don't see why time is important. However, there is no reason you cannot do both and see what difference it ma...

Time Domain Signal for neural network

If you have rpm I don't see why time is important. However, there is no reason you cannot do both and see what difference it ma...

mer än ett år ago | 0

| accepted

Answered

Adding hidden layers to a patternnet hurts accuracy?

The global minimum is achievable with a single hidden layer. With more hidden layers you add more local minima; most of which ...

Adding hidden layers to a patternnet hurts accuracy?

The global minimum is achievable with a single hidden layer. With more hidden layers you add more local minima; most of which ...

mer än ett år ago | 0

| accepted

Answered

Training neural network - Forward Pass

You are very mixed up. I suggest going to the library and finding a good elementary NN book. Obviously, the appropriate info is...

Training neural network - Forward Pass

You are very mixed up. I suggest going to the library and finding a good elementary NN book. Obviously, the appropriate info is...

mer än ett år ago | 1

Answered

Hello, I'm working with artificial neural network.

Three layers are sufficient: input/hidden/output The input layer is NOT a neuron layer. The number of input nodes is the dimens...

Hello, I'm working with artificial neural network.

Three layers are sufficient: input/hidden/output The input layer is NOT a neuron layer. The number of input nodes is the dimens...

mer än ett år ago | 0

| accepted

Answered

Why neural network gives negative output ?

How different is the new data (e.g., Mahalanobis distance)? If you know the true outputs, how do the error rates compare? If y...

Why neural network gives negative output ?

How different is the new data (e.g., Mahalanobis distance)? If you know the true outputs, how do the error rates compare? If y...

mer än ett år ago | 0

| accepted

Answered

Rsq from NMSE in NN

NMSE = mse(trnopdb-net(trnipdb))/MSE00 i.e., NO TRANSPOSES 2. Rsq = R^2 3. Yes. Use separate calculations fo...

Rsq from NMSE in NN

NMSE = mse(trnopdb-net(trnipdb))/MSE00 i.e., NO TRANSPOSES 2. Rsq = R^2 3. Yes. Use separate calculations fo...

mer än ett år ago | 1

| accepted

Answered

HOW DO I SEARCH IN ANSWERS ???

Oh! It only opens up at the top of the page if the page is sufficiently wide. Since I often use large type and 2 pages per scre...

HOW DO I SEARCH IN ANSWERS ???

Oh! It only opens up at the top of the page if the page is sufficiently wide. Since I often use large type and 2 pages per scre...

mer än ett år ago | 0

| accepted

Answered

Interpolation using Neural Networks

Plot the data. Look at the plots Are there regions that are seasonal? Separate the data that is relevant to your problem Ca...

Interpolation using Neural Networks

Plot the data. Look at the plots Are there regions that are seasonal? Separate the data that is relevant to your problem Ca...

mer än ett år ago | 0

| accepted

Answered

How to plot only few classes for confusion matrix?

Oviously, you have to subsample the original matrices. Greg

How to plot only few classes for confusion matrix?

Oviously, you have to subsample the original matrices. Greg

mer än ett år ago | 0

Answered

Open loop Training performance and closed loop training performance are good but multi-step prediction is bad. Reason?

You are not considering information from the autocorrelation fuction. Hope this helps Greg

Open loop Training performance and closed loop training performance are good but multi-step prediction is bad. Reason?

You are not considering information from the autocorrelation fuction. Hope this helps Greg

mer än ett år ago | 0

Answered

Formula for two layer FFNN

y1 = b1 + IW1 * x y2 = b2 + LW2 * tanh( y1 ) y3 = b3 + LW3 * tanh( y2 ) = b3 + LW3 * tanh( b2 + LW2 * tanh( b1 + IW1 * x ...

Formula for two layer FFNN

y1 = b1 + IW1 * x y2 = b2 + LW2 * tanh( y1 ) y3 = b3 + LW3 * tanh( y2 ) = b3 + LW3 * tanh( b2 + LW2 * tanh( b1 + IW1 * x ...

mer än ett år ago | 0

| accepted

Answered

Input and target have different number of sampel

Train and TTrain have to be transposed. Hope this helps. THANK YOU FOR FORMALLY ACCEPTING MY ANSWER Greg

Input and target have different number of sampel

Train and TTrain have to be transposed. Hope this helps. THANK YOU FOR FORMALLY ACCEPTING MY ANSWER Greg

mer än ett år ago | 0

| accepted

Answered

How to calculate accuracy for neural network algorithms?

I normalize the mean-square-error MSE = mse(error) = mse(output-target) by the minimum MSE obtained when th...

How to calculate accuracy for neural network algorithms?

I normalize the mean-square-error MSE = mse(error) = mse(output-target) by the minimum MSE obtained when th...

mer än ett år ago | 0

| accepted

Answered

Neural Network input and targets have different of samples

Transpose both matrices. Thank you for formally accepting my answer Greg

Neural Network input and targets have different of samples

Transpose both matrices. Thank you for formally accepting my answer Greg

mer än ett år ago | 0

| accepted

Answered

How these plots (Performance, Training state, Regression) shows the training performance? How to figure out the training rate from these plots?

Training data plots are useful. However, there is no indication of how good the net will perform on nontraining data (THE TRUE ...

How these plots (Performance, Training state, Regression) shows the training performance? How to figure out the training rate from these plots?

Training data plots are useful. However, there is no indication of how good the net will perform on nontraining data (THE TRUE ...

mer än ett år ago | 0