Tagged Questions
0
votes
0answers
13 views
How does MATLAB AutoEncoder scale data?
I found in the documentation of AutroEcnoder that:
Indicator to rescale the input data, specified as the comma-separated
pair consisting of 'ScaleData' and either true or false.
Autoencoders ...
0
votes
0answers
31 views
Get middle output from Stacked Autoencoder in Matlab
I have a stacked Autoencoder network and I'd like to get the middle outputs of the tuned network.
My input data is 1620 x 3000 and my target data is 12 x 3000. My test data is 1620 x 500.
I have a ...
0
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0answers
94 views
How does feature extraction work in a sparse autoencoder?
https://www.mathworks.com/help/nnet/examples/training-a-deep-neural-network-for-digit-classification.html
In the above tutorial, how do we get the image features in the first hidden layer?
This is a ...
0
votes
1answer
418 views
Simple denoising autoencoder for 1D data in Matlab
I'm trying to set up a simple denoising autoencoder with Matlab for 1D data. As currently there is no specialised input layer for 1D data the imageInputLayer() function has to be used:
function net = ...
0
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0answers
31 views
how can I get out of this error “The dimensions of the networks do not match for stacking.”
I trying to build an autoencoder on employees dataset which consist of 14999x10.I used 3 layers to construct the autoencoder but when I try to stack the together using
stackednet=stack(autoenc1,...
0
votes
1answer
69 views
RBM pretraining weights from Hinton paper code for weights of MATLAB native feedforwardnet toolbox
I want to use RBM pretraining weights from Hinton paper code for weights of MATLAB native feedforwardnet toolbox.
Anyone can help me how to set or arrange the pre-trained weight for feedforwardnet?
...
1
vote
1answer
140 views
MATLAB: How can we change the cost function of Autoencoder
I want to change the cost function of Autoencoder in MATLAB instead of the traditional cost function that minimizes the reconstruction error. Can I do it directly by explicitly mentioning it somewhere?...
0
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0answers
172 views
Colour image classification using Stacked Autoencoders
I want to use Stacked Autoencoders for colour image classification. The example given on matlab site for image classification of MNIST dataset is only for black and white images which has only one ...
0
votes
1answer
383 views
Stacked Sparse Autoencoder parameters
I work on Stacked Sparse Autoencoders using MATLAB.
Can anyone please suggest what values should be taken for
Stacked Sparse Autoencoder parameters:
L2 Weight Regularization ( ...
0
votes
1answer
176 views
Unsupervised training of sparse autoencoders in matlab
I've tried to follow the example provided at mathworks for training a deep sparse autoencoder (4 layers), so i pre-trained the autoencoders separately and then stacked then into a deep network. When i ...
0
votes
1answer
108 views
Errors out of memory running Matlab Autoencoders on 10^5 sparse matrix
I have a 10^5 square sparse matrix called pbAttack. Each element represents if there is connection between node i and node j. If there is connection, pbAttack(i,j) = 1. Otherwise, pbAttack (i,j) = 0. ...
0
votes
0answers
93 views
Matlab - autoencoder for speech signal
I want to use the trainAutoencoder function from matlab to find the 30 main patterns of 300 speech signals.
I tried to use this function, and use plotWeigths to see the patterns (weigths) but it ...
0
votes
0answers
259 views
Visualize weights of stacked Autoencoder
I trained a stacked Autoencoder. The dimension of weight of first hidden layer is ( SizeHiddenLayer1 x SizeInputLayer) so visualization of this weight is simple because the size of input data and ...
1
vote
0answers
269 views
MATLAB autoencoder learning the constant function
I'm trying to train a basic autoencoder in MATLAB. My data is 430 ten-dimensional points, and my autoencoder code like
n_features = 25;
autoenc = trainAutoencoder(data, n_features, ...
'...
2
votes
1answer
2k views
Function approximation using Autoencoder in MATLAB
I have a simple non-linear function y=x.^2, where x and y are n-dimensional vectors, and the square is a component-wise square. I want to approximate y with a low dimensional vector using an auto-...
1
vote
0answers
110 views
Unsupervised Neural Network with Independent hidden Activations: How to implement entropy or kurtosis penalty?
In brief:
How do I implement ICA-like entropy or kurtosis penalty term for the cost and back-propagation of my unsupervised neural network (I'm using stacked sparse Autoencoders)?
In details:
I've ...
5
votes
2answers
1k views
Using large input values with Auto Encoders
I have created an Auto Encoder Neural Network in MATLAB. I have quite large inputs at the first layer which I have to reconstruct through the network's output layer. I cannot use the large inputs as ...
