Anderson

Aktiv seit 2014

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How to add rows to a mtrix following a certain condition?
Suppose the following matrix r= [0; 1; 1.5; 1.6; 2; 10.4; 15.5]. How to add rows which are in the interval floor(r):0.1:floor...

mehr als 8 Jahre vor | 2 Antworten | 0

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How to add rows to a mtrix following a certain condition?
I found the problem. r=unique(r, 'rows', 'stable'); for i=1:size(r,1); p(i,:) = floor(r(i)):0.1:floor(r(i))+1; end q = ...

mehr als 8 Jahre vor | 0

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How to divide large data in small intervals?
How to divide a large matrix into small intervals? For example, take the matrix [1 1; 1 2; 2 3; ...;5 100; 6 100; ...; 1 1....

mehr als 8 Jahre vor | 2 Antworten | 0

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How to reduce this matrix?
How to reduce this matrix? Suppose that M=[1 0.1 1.1; 1 0.1 1.1; 3 0.1 1.2; 2 0.2 3; 1 2 4; 2 2 4; 2 3 5]; based on the se...

mehr als 8 Jahre vor | 1 Antwort | 0

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How does the Box-Cox Transformation in Matlab work?
What is the explicitly Log-Likelihood Function (LLF) maximized? Are the variance and mean values computed from the data?

fast 9 Jahre vor | 1 Antwort | 0

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Does Matlab has relative square error available in Neural Network toolbox?
I have seen that MSE, SSE, MAE and SAE are possible training functions of a neural network in Matlab. Does it have relative squa...

fast 9 Jahre vor | 2 Antworten | 0

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Is good to repeat the same sample in the training of the neural network?
Does the neural network improve repeating the same samples values during training?

fast 9 Jahre vor | 1 Antwort | 0

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Are there features that the input and target values should follow before training in a neural network?
Even with normalization or mapping in a range [-1,1] before training, I have seen that a good scaling of the data may improve th...

fast 9 Jahre vor | 1 Antwort | 0

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How to define error weights in Neural Network?
I want to minimize a mean squared weighted deviation in a neural network. The weights are different for each sample. How can ...

fast 9 Jahre vor | 2 Antworten | 0

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Is the mse of the testing set in the neural network computed simultaneously with the mse of the training and validation sets?
In the performance plot, there are three curves: training, validation, testing. Is the mse of the testing set computed simultane...

etwa 9 Jahre vor | 1 Antwort | 0

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Is possible to normalize just the training data instead of the whole data using Neural Network toolbox?
Using the Matlab functions, it is possible to normalize the input and output data that will feed the Neural Network. However, is...

etwa 9 Jahre vor | 2 Antworten | 0

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When I generate a Matlab function of a neural network, it comes with the normalization/re-normalization constants. Will these constants affect the neural network performance on another data set? Why?
The normalization/re-normalization (for example, mapping the data to [-1,1] or [0,1]) is built for the training data. What does ...

etwa 9 Jahre vor | 1 Antwort | 0

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Neural Network in loops: How can I set up a loop to train at least 10 neural networks with the same parameters and save only the best performance, regression and histogram error, and the matrix-only MATLAB function for neural network code?
Hi, How can I set up a loop to train at least 10 neural networks with the same parameters and save only the best perform...

etwa 9 Jahre vor | 2 Antworten | 0

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Neural Network: what does mean when the R-value is close to 1, but MSE (mean squared error) is large?
Hi, Considering a trained neural network, what does mean when the R-value is close to 1, but MSE (mean squared error) is l...

etwa 9 Jahre vor | 1 Antwort | 0

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Neural Network - net.divideFcn = 'divideind'
Hi, I am trying to use "net.divideFcn = 'divideind'". In my case, I want to merge two different range of indices, e.g., ...

etwa 9 Jahre vor | 1 Antwort | 0

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How can put eigenvalues in ascending order?
Hi, I am using something like [V,D] = eig(S) and I would like the eigenvalues in ascending order in the diagonal. V, D and S ...

etwa 10 Jahre vor | 1 Antwort | 0

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How can I make my loop works?
How can I make my loop works? I know P0 (my initial guess) P0 = 3.5378 -2.3325 -2.3325 3.5378 X = ...

etwa 10 Jahre vor | 1 Antwort | 0

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Anderson

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