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...

6 Monate ago | 0

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...

6 Monate ago | 0

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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...

6 Monate ago | 0

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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...

6 Monate ago | 1

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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...

6 Monate ago | 0

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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...

6 Monate ago | 0

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How to plot only few classes for confusion matrix?
Oviously, you have to subsample the original matrices. Greg

6 Monate ago | 0

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

6 Monate ago | 0

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 ...

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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

6 Monate ago | 0

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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...

6 Monate ago | 0

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Neural Network input and targets have different of samples
Transpose both matrices. Thank you for formally accepting my answer Greg

6 Monate ago | 0

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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 ...

6 Monate ago | 0

Validation check = 0 for traingdm
What you are worrying about is irrelevant. Your data is so good you don't even need a validation subset.The main purpose of a va...

7 Monate ago | 1

Expressing equation in terms of sin/cos
If you substitute your solutions into LHS and get the RHS, then it is possible. Greg

7 Monate ago | 0

How to decide window size for a moving average filter?
I'm very surprised that none of the previous responses mentioned 1. Determine characteristic self correlation lengths usi...

7 Monate ago | 0

finding optimal neural network architecture using genetic algorithms
0. The genetic approach is a waste of time. It takes too long. 1.Typically, a single hidden layer is sufficient. 2. Minimize t...

7 Monate ago | 0

Neuron Network input variables-Missing data
Sorry: You have to predict the missing data as best you can. Greg

7 Monate ago | 0

Why my network is not giving the desired output
Design(training+validation), test and new data should all have the same summary statistics BEFORE NORMALIZATION. This may requir...

7 Monate ago | 0

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How to predict future responses y(t + 1) from the training of a narxnet network with past data of x (t) and y (t)? (NARXNET)
YOU DO NOT HAVE X and Y !!! YOU HAVE X and T where T = Ydesired Hope this helps Thank you for formally accepting m...

7 Monate ago | 1

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Testing a Backpropagation Neural Network
You are probably OVERTRAINING AN OVERFIT NET OVERFITTING: Using more unknown hidden nodes than number ...

7 Monate ago | 0

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The performance of hidden neurons
I think I misinterpreted the question. Now I think you mean when I increase the number of hidden nodes from 4 to 5 why do I star...

7 Monate ago | 0

Crossentropy loss function - What is a good performance goal?
These equations are not necessarily precise. For example: data = design + test design = training + validation In partic...

8 Monate ago | 0

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How can two neural networks be compared for regression based on training and testing results ?
The MATLAB default is training/validation/testing fractions of 0.7/0.15/0.15 Typically, the performance depends on a 1. A...

8 Monate ago | 0

what types of Network and training are suitable for returning a more precise value?
Plot your targets vs your inputs to see if some of the inputs are not worth using. and/or you can try rejecting inputs based ...

8 Monate ago | 0

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Issue while mapping weights to a New Feedforward Neural network created using newff
You need to add another component equal to unity to account for a bias weight. Thank you for formally accepting m answer. ...

8 Monate ago | 0

how to adjust derivatives of backpropagation according to custom error function
Your error function is not at a minimum when output = target Why did you not use the standard E = (output - target)^2 ...

8 Monate ago | 0

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How to compute gradients using the Neural Network Toolbox software?

8 Monate ago | 0

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