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Questions tagged [backpropagation]

Backpropagation is a method of the gradient computation, often used in artificial neural networks to perform gradient descent.

Backpropagation is a method of the gradient computation, often used in artificial neural networks to perform gradient descent. It led to a “renaissance” in the field of artificial neural network research.

In most cases, it requires a teacher that knows, or can calculate, the desired output for any input in the training set. The term is an abbreviation for "backward propagation of errors".

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Python - Neural Network Approximating Sphere Function

I am new to neural networks and I am using an example neural network I found online to attempt to approximate the sphere function(the addition of a set of numbers squared) using back propagation. The initial code is: class NeuralNetwork(): def…
hezzag
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Does Bishop's book imply that a unit neuron feed to itself in backpropagation?

I just read Bishop book's Pattern Recognition and Machine Learning, I read the chapter 5.3 about the backpropagation, it said in his book that, In general feed-forward network, each unit computes a weighted sum of its inputs of the form…
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Getting NaN values in neural network weight matrices

**I am trying to develop a feedforward NN in MATLAB. I have a dataset of 12 inputs and 1 output with 46998 samples. I have some NaN values in last rows of Matrix, because some inputs are accelerations & velocities which are 1 & 2 steps less…
Thulasi Ram Tammu
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Multi-Layer Neural Network - Training Process

I'm building a multilayer neural network. I have question regarding training process, I have a set of training-data with desired outputs. I am using Backpropagation algorithm for updating the connections weights. should the network train…
Makaveli
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Unusual results from Neural Network

I wrote a simple Feed Forward Artificial Neural Network for Symbol Recognition. I have a Set of 6 possible Symbols in a 5x5 grid of pixels. These are {X, +, -, \, /, |} For example X would be: X = [1,0,0,0,1, 0,1,0,1,0, 0,0,1,0,0, …
Greg Peckory
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Backpropagation - Neural Networks

How does the output value of step 1 result in the value of "0.582"? I am looking at an example of the usage of backpropagation in order to have a basic understanding of it. However I fail to understand how the value "0.582" is formed as the output…
Ron
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Implement bias neurons neural network

I implemented bias units for my neural network with gradient descent. But I'm not 100% sure If I've implemented it the right way. Would be glade if you can quickly look through my code. Only the parts with if bias: are important. And my second…
Peter234
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Bias Parameter in MLP in spark

I am using MLP of spark mlib for predictive analysis. I want to give more weightage to one of the output class and i am using Multilayer perceptron classifier for prediction. As given in the documentation here Spark Multilayer perceptron…
deenbandhu
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how to propagate error from the conv-layer to previous layer in Lenet-5 CNN

Recently I'm trying to implement the Lenet-5 CNN. But I stuck in how to propagate error from the conv-layer to previous layer, for example, from C3 layer to S2 layer. Could anybody please help me?
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Backpropagation neuron networks

Hi I playing with neural nets right now. I made kind of reimplementation of this tutorial: http://www.ai-junkie.com/ann/evolved/nnt5.html, but with fishes and food and also different programing language. But the point is same. I have bunch of…
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integrate BP neural network with PSO

I would like to use PSO to optimize BP neural network weights for prediction of breast cancer on Matlab. there is no option in the neural toolbox to do that. and after searching, i found the memetic approach but I don't now how to use it throw…
juliana
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Simple Neural Network with MNIST stuck at 17% missclasification error

Hello Im putting my code for inspection because Ive been playing with my neural network implementation in python for a few weeks and I cant seem to reach a misclasification error below 17% some times 16%. ve been trying different learning rate…
MeMoVsGodzilla
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Artificial Neural Network Back Propagation testing

I have developed a code for ANN BP to classify snore segments. I have 10 input features and 1 hidden layer with 10 neuron and one output neuron. I denoted 1 as no snore and 0 as snore segment. I have 3000 segments and among them 2500 are no snore…
Odrisso
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Backpropagation Neural Network doesn't learn properly

I'm coding neural network and I have trouble with understanding and coding Backpropagation, but it doesn't learn properly. I don't know where is problem in my Backpropagation function. This is my error function L = plogq + (1−p)log(1−q) And my…
Filip V
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Neural network backpropagation (1 output) gets no where?

I have a neural network with a lot of inputs, and i want to train it to realise that only 1 of the inputs matter. First i train it with input[1]=1 and given result 10 then i train with exact same inputs except input[1] = 0 and given result being…
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