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

plus de 2 ans 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

plus de 2 ans 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 ...

plus de 2 ans 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

plus de 2 ans 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...

plus de 2 ans 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

plus de 2 ans 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 ...

plus de 2 ans ago | 0

Answered

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...

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...

plus de 2 ans ago | 1

Answered

Expressing equation in terms of sin/cos

If you substitute your solutions into LHS and get the RHS, then it is possible. Greg

Expressing equation in terms of sin/cos

If you substitute your solutions into LHS and get the RHS, then it is possible. Greg

plus de 2 ans ago | 0

Answered

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...

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...

plus de 2 ans ago | 0

Answered

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...

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...

presque 3 ans ago | 0

Answered

Neuron Network input variables-Missing data

Sorry: You have to predict the missing data as best you can. Greg

Neuron Network input variables-Missing data

Sorry: You have to predict the missing data as best you can. Greg

presque 3 ans ago | 0

Answered

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...

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...

presque 3 ans ago | 0

| accepted

Answered

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...

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...

presque 3 ans ago | 1

| accepted

Answered

Testing a Backpropagation Neural Network

You are probably OVERTRAINING AN OVERFIT NET OVERFITTING: Using more unknown hidden nodes than number ...

Testing a Backpropagation Neural Network

You are probably OVERTRAINING AN OVERFIT NET OVERFITTING: Using more unknown hidden nodes than number ...

presque 3 ans ago | 0

| accepted

Answered

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...

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...

presque 3 ans ago | 0

Answered

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...

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...

presque 3 ans ago | 0

| accepted

Answered

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...

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...

presque 3 ans ago | 0

Answered

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 ...

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 ...

presque 3 ans ago | 0

| accepted

Answered

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. ...

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. ...

presque 3 ans ago | 0

Answered

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 ...

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 ...

presque 3 ans ago | 0

| accepted

Answered

How to compute gradients using the Neural Network Toolbox software?

help gradient doc gradient Thank you for formally accepting my answer Greg

How to compute gradients using the Neural Network Toolbox software?

help gradient doc gradient Thank you for formally accepting my answer Greg

presque 3 ans ago | 0

Answered

An error occurred while trying to determine whether "readData" is a function name.

>> help readData readData not found >> doc readData SUCCESS !!! Hope this helps THANK YOU FOR FORMALLY ACCEPTING MY A...

An error occurred while trying to determine whether "readData" is a function name.

>> help readData readData not found >> doc readData SUCCESS !!! Hope this helps THANK YOU FOR FORMALLY ACCEPTING MY A...

presque 3 ans ago | 0

Answered

Create neural Network with multiple outputs

See my comment. Greg

Create neural Network with multiple outputs

See my comment. Greg

presque 3 ans ago | 0

| accepted

Answered

Overfitting of Regression Plot for a Feedforward Neural Network

OVERFITTING IS NOT "THE" PROBLEM !!! In general, the problem is OVERTRAINING an overfit net. My solution is simple: DO NOT OV...

Overfitting of Regression Plot for a Feedforward Neural Network

OVERFITTING IS NOT "THE" PROBLEM !!! In general, the problem is OVERTRAINING an overfit net. My solution is simple: DO NOT OV...

presque 3 ans ago | 0

| accepted

Answered

Neural Network Last Layer Shows a Different Number of Outputs

Line 2: target, not output trainFcn is undefined. I get 15, not 13 in the figure Hope this helps. Thank you for formal...

Neural Network Last Layer Shows a Different Number of Outputs

Line 2: target, not output trainFcn is undefined. I get 15, not 13 in the figure Hope this helps. Thank you for formal...

presque 3 ans ago | 0

Answered

When I should stop training a neural network?

The danger is OVERTRAINING an OVERFIT NET. There are several approaches. 1. PREVENT OVERFITTING the I-H-O net by ...

When I should stop training a neural network?

The danger is OVERTRAINING an OVERFIT NET. There are several approaches. 1. PREVENT OVERFITTING the I-H-O net by ...

presque 3 ans ago | 1

| accepted

Answered

Artificial Neural Network questions

The typical NN has a set of input nodes ( which for some reason is not defined to be a layer !!! ), a middle layer and an outpu...

Artificial Neural Network questions

The typical NN has a set of input nodes ( which for some reason is not defined to be a layer !!! ), a middle layer and an outpu...

presque 3 ans ago | 0

| accepted

Answered

Do Multiple Output Neural Networks share the same weights and biases?

The similarity or orthogonality of the outputs tends to be irrelevant. If two set of outputs are not caused by a significant ...

Do Multiple Output Neural Networks share the same weights and biases?

The similarity or orthogonality of the outputs tends to be irrelevant. If two set of outputs are not caused by a significant ...

presque 3 ans ago | 0

| accepted

Answered

What is the difference between pca and processpca commands?

help pca doc pca help processpca doc processpca Hope this helps Thank you for formally accepting my answer Greg

What is the difference between pca and processpca commands?

help pca doc pca help processpca doc processpca Hope this helps Thank you for formally accepting my answer Greg

presque 3 ans ago | 0

| accepted