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Questions tagged [dbn]

Deep Belief Networks, a key concept in contemporary neural networks.

Deep Belief Networks, a key concept in contemporary s.

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SupervisedDBNClassification' object has no attribute 'classes_'

I am using supervisedDBN learning code which is deep learning architecture, i customize the below code and got the following error... I am working on KDD99 Network security dataset to analyze multiple attacks. but have the following error in code.…
Uzair
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Training an RBM with Denoising Contrastive Divergence ?

Just recently, I was wondering why nobody seems to use denoising training for Restricted Boltzmann Machine (RBM) and Convolutional-RBM (CRBM) models. This is very powerful for auto-encoders (Denoising Auto-Encoders (DAE) and Stacked-DAE (SDAE)). I…
Baptiste Wicht
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Deep Belief Network inference: hidden layers need random number generator?

I am learning Deep Belief Network and Restricted Boltzmann Machine. In training DBN (CD-1, greedy, layer-wise), inputs to the second, third, and nth RBM should be stochastic binary (0 or 1) and not probability? As for the inference process in DBN,…
Yoko
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Deep Belief Network with Denoising Auto Encoder in Tensorflow

I need to implement a classification application for neuron-signals. In the first step, I need to train a denoising autoencoder(DAE) layer for signal cleaning then, I will feed the output to a DBN network for classification. I tried to find support…
DigitalFox
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scikit-learn DBN encoding string labels

I am quite new to both python and scikit-learn. My goal is to get a classification working that should the divide into 6 different string labels with a deep belief net. Here are some samples of my…
mlang
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Custom operation implementation for RBM/DBN with tensorflow?

Since Google released out tensorflow, it becomes kind of trend in the current deep learning selections. I'd like to do some experiments about RBM/DBN (Restricted Boltzmann Machine/Deep Belief Network), I've made some attempt by myself and kind of…
myme5261314
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data propagation through restriced boltzmann machine

In RBM, it makes all relationships within node in probability. then how data can be propagated through RBM? just first order sampling? doesnt then have too much fluctuation? or does it work like feed forward mlp? (ie. hj = \sum_i vi * wij) but in…
forsythia
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Implementing GB-RBMs for real-valued data

I am trying to implement a Deep Belief Network for speech recognition. And hence, need the first layer of RBM to have gaussian visible units. I used @Andrej Karpathy's matrbm (https://code.google.com/p/matrbm/) and made some changes to convert the…
Nihar Sarangi
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Deep Belief Networks vs Convolutional Neural Networks performance on non-Image Classification Tasks

In the paper Improved Classification based on Deep Belief Networks, the authors have stated that for better classification, generative models are used to initialize the model and model features before training a classifier. Typically they are needed…
Prishita Ray
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how to plot real time line graph from dbn classifier train

I'm working on a face recognition system using the DBN algorithm. when training data, the system will produce an error according to n-epoch. I want to make an error graph plot based on n-epoch Training Code classifier =…
iqbal putra
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Deep Belief Network for Function Approximation

I am using the deep neural network toolbox developed by Masayuki Tanaka at following link https://www.mathworks.com/matlabcentral/fileexchange/42853-deep-neural-network. Now I'm trying to use the deep belief network to do the function approximation.…
user6112462
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Stacking ReLU RBM into a DBN

I'm implementing a Restricted Boltzmann Machine with Rectified Linear Units. I haven't found a simple implementation anywhere so wanted to ask if somebody would kindly verify the design. Here is the CD1 calculation: def propup(self, vis): …
valend.in
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How to handle negative input data in deep belief networks

In my data, I have a column with negative and positive values. Here negative value means how much some things are missing and positive values means unexpected additional things and 0 means neutral which is always expected value. So how can I use…
asdfkjasdfjk
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Pretraining error increases in each epoch in Deep Belief Network

I am using this implementation of DBN. http://deeplearning.net/tutorial/code/DBN.py I am using ecg data to train the model which contains 100 float values (in milivolt unit) per row. When I run this implementation the pretraining cost goes on…
Sayantan Ghosh
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ValueError Theano

I am using a DBN classification code. I have one output value which is an integer(value of the output integer can be anything 110,12 etc). So basically I am trying to predict something using the classification code by setting its no_of_outputs=1.…
Rimsha
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