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33 views

How do errors make sense for hidden layers in artificial neural networks?

Its pretty clear for the output layer, since what we do is we compare the output with our prototype and calculate the error. But how does error make sense for hidden layers, What is considered to be ...
-1
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0answers
53 views

Backpropagation in layman terms [on hold]

I've been studying neural networks, and I'm beginning to understand the basics. I know what the backpropagation algorithm does. It feeds sample input and calculates an error against a given output. ...
20
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4answers
1k views

Calendar/Planning algorithm

I'm facing a problem I'm not sure how to approach. I have to generate a calendar for employees, each of them having specific work constraints (some personal, some common) What I'm working with : I ...
2
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1answer
62 views

To what values should you initialize the neurons and connection strengths in a neural network?

The values of all of the neurons in my neural network are initialized to 0 and the connection strengths between the neurons are set to randomly generated floats, between 0 and 1. I have seen other ...
2
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1answer
55 views

How can you write an activation function in a neural network to handle a layer architecture of arbitrary dimensions?

I am making a neural network in Clojure that can take an array of integers,and return a data structure representing the layers of a neural network: so (make-layers [1 4 5]) would evaluate to: [[0] ...
1
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1answer
47 views

An Introductory Tutorial for Neural Net Backpropagation with Simplified Math

I built a neural net, and planned on optimizing the weights using a genetic algorithm. I was informed though, that this isn't a good idea, and to look into backpropagation. I searched around, and ...
2
votes
1answer
96 views

Is the output of a neural net supposed to have had the activation function applied to it?

TL; DR: Is the output from a feed-forward neural a direct result of the activation function? I.e: If the activation function is the sigmoid function, will the output always be between 0 and 1? I'm ...
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0answers
45 views

How to evaluate a recurrent connection in an artificial neural network?

I just can't understand how should I compute the output of a neural network, which contains a recurrent connection. So here is an example: (i_1,2 are the input values, w_1,2,3,r are the ...
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0answers
24 views

Distributed versus Sparse encoding for Neural Network Input

This is not a theoretical question, but an actual question which will reflect my implementation in C++ of a Knowledge Representation classifier. The intended ANN is in fact a binary RBM. My data, is ...
2
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0answers
53 views

What parallelization methods can make neural nets train faster?

A fairly straightforward way (on a theoretical level, at least) of parallelizing artifical neural networks (ANNs) would be to divy up the batches of training examples during every epoch so that ...
2
votes
1answer
138 views

What type of neural network is suitable for simulating brain of virtual organism? [closed]

A while ago I was experimenting with evolving virtual creatures using neural network + genetic algorithm, but that didnt go well (simulation speed was too slow, mainly because bad programming habbits ...
1
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0answers
89 views

Neural network converges to 0.5 for XoR

I'm coding a neural network in C for an OCR project. Before testing with character recognition, I'm making it learn the XoR operation. Although, the results I'n getting always converges to 0.5 instead ...
0
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2answers
100 views

Could one sample be enough for a perceptron training?

I need to compare a picture and decide whether or not it is similar to another one. In this case, I would like to use a simple perceptron that compares pixelmaps of both pictures. But I have only very ...
2
votes
1answer
153 views

Support Vector Machines as Neural Nets?

This is more of a conceptual question. I have learned about Neural Nets, and I have some clue as to how Support Vector Machines work. I read somewhere however that given the appropriate kernel (is ...
1
vote
2answers
307 views

Neural network input preprocessing

It's clear that the effectiveness of a neural network depends strongly on the format you give it to work with. You want to pre-process it into the most convenient form you can algorithmically get to, ...
5
votes
2answers
315 views

How to solve this problem- Neural Net? Fuzzy? Other?

Hi I have a programming problem that I would like to solve using some artificial intelligence technique. I really dont know where to start. I would like some guidance as to what methodology to pursue. ...
1
vote
1answer
1k views

How to design a calculator from scratch [closed]

A basic calculator can perform a wide variety of operations. How does the claculator 'get' the concept of adding two numbers in the same way a human does? I dont think people that make claculators ...
6
votes
5answers
494 views

Type of AI to tackle this problem?

I posted this on stackoverflow but want to get your recommendations as well as a user on overflow recommended I post it here. I'm going to say from the beginning that I am not a programmer, I have a ...
1
vote
1answer
60 views

Create association between informations

I deployed a project some days ago that allow to extract some medical articles using the results of a questionnaire completed by a user. For instance, if I reply on questionnaire I'm affected by ...
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2answers
999 views

Can neural network discover rng patterns

Can neural network find connections beetween numbers generated by random number generator without knowing about it's seed and predict this rng's next numbers with more sucess then randomly guessing? I ...
6
votes
1answer
141 views

How to determine the source of a request in a distributed service system?

Map/Reduce is a great concept for sorting large quantities of data at once. What to do if you have small parts of data and you need to reduce it all the time? Simple example - choosing a service for ...
1
vote
4answers
866 views

Sign Language Recognition [closed]

I am a final year undergraduate student of Information Technology. My team and I have taken up "Sign Language Recognition" as our Final Year Project. We have just started with it and we are in the ...
10
votes
4answers
6k views

What is a Neural Network in simple words [closed]

Can you please explain neural networks in simple words with an example?
4
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2answers
310 views

Can symbolic AI 'learn' a data model?

Perceptrons, a simple form of supervised machine learning, must be trained with a set of known good inputs before they can "learn" by adjusting internal weights assigned to inputs, based on the ...