Questions tagged [neural-network]

Artificial neural networks (ANN), are composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows information to propagate through the network to solve artificial intelligence problems without the network designer having had a model of a real system.

Filter by
Sorted by
Tagged with
1
vote
2answers
3k views

Neural networks with non-negative weights [closed]

Could you tell me, are there any techniques for building neural networks with non-negative weights?
1
vote
0answers
86 views

Prove Reccurrent Neural Network can exhibit oscillatory behavior

I understand how recurrent neural networks work, however I'm trying to build a deep intuitive understanding of their behavior which is difficult for me because they exhibit such complex behaviors. ...
1
vote
1answer
3k views

Theano/Lasagne/Nolearn Neural Network Image Input

I am working on image classification tasks and decided to use Lasagne + Nolearn for neural networks prototype. All standard examples like MNIST numbers classification run well, but problems appear ...
6
votes
1answer
1k views

Neural Network Golf: smallest network for a certain level of performance

I am interested in any data, publications, etc about what is the smallest neural network that can achieve a certain level of classification performance. By small I mean few parameters, not few ...
1
vote
0answers
203 views

Better approach for handwriting recognition?

I am trying to write an ANN in python for handwriting recognition by mouse movements. ( like identify characters we draw in paint app n convert it to text) The question might seem that I haven't ...
1
vote
2answers
746 views

How can the performance of a neural network vary considerably without changing any parameters?

I am training a neural network with 1 sigmoid hidden layer and a linear output layer. The network simply approximates a cosine function. The weights are initiliazed according to Nguyen-Widrow ...
4
votes
2answers
850 views

How are neural nets related to Fourier transforms?

This is an interview question How are neural nets related to Fourier transforms? I could find papers that talk about methods to process the Discrete Fourier Transform (DFT) by a single-layer ...
4
votes
1answer
834 views

How to select topology for neural network?

I was given a target function to design neural network and train: (y = (x1 ∧ x2) ∨ (x3 ∧ x4)) The number of input and number of output seems obvious (4 and 1). And the training data can use truth ...
42
votes
2answers
41k views

How to prepare/augment images for neural network?

I would like to use a neural network for image classification. I'll start with pre-trained CaffeNet and train it for my application. How should I prepare the input images? In this case, all the ...
1
vote
2answers
801 views

training neural net with multiple sets of time-series data

I have the following data ($x^1_i$, $y^1_i$) for $i=1,2,...N_1$ ($x^2_i$, $y^2_i$) for $i=1,2,...N_2$ ... ($x^m_i$, $y^m_i$) for $i=1,2,...N_m$ Is it possible to train a neural net to produce ...
0
votes
2answers
89 views

Should I use epochs > 1 when training data is unlimited?

If I have virtually endless training data (it's synthesized) is there still purpose in having epochs? I.e. training on the same samples multiple times?
5
votes
9answers
19k views

Machine learning toolkit for Excel

Do you know of any machine learning add-ins that I could use within Excel? For example I would like to be able to select a range of data and use that for training purposes and then use another sheet ...
1
vote
1answer
87 views

normalize identification values properly

I'm building a neural network to analyze a business' sales. I'm normalizing all input values to the range {0,1}. I'm struggling with the day of the week column. ...
1
vote
1answer
118 views

Compare Neural Network generalization results

I'm trying to develop my neural network with both early stopping and bayesian regularization (matlab implementation, lm algorithm is used for both). Since in bayesian regularization I have not the ...
1
vote
2answers
492 views

Neural Network Hidden Neuron Selection Strategy

I'm trying to determine what is the best number of hidden neurons for my MATLAB neural network. I was thinking to adopt the following strategy: Loop for some values of hidden neurons, e.g. 1 to 40; ...
3
votes
2answers
1k views

Training Neural Networks with unknown length of input

I'm currently going into the world of machine learning and Neural Networks, thanks to synaptic (js) that interests me a lot. So I read a lot, wikipedia links and synaptic's NN 101, but there's a lot ...
14
votes
2answers
4k views

Visualizing deep neural network training

I'm trying to find an equivalent of Hinton Diagrams for multilayer networks to plot the weights during training. The trained network is somewhat similar to a Deep SRN, i.e. it has a high number of ...
0
votes
0answers
256 views

Analyze paragraphs using Neuroph

Currently we are regularly analyzing sets of paragraphs every month. I would like to automate this and split each paragraphs into chunks of data. To do this I would like to employ a neural network. ...
3
votes
0answers
298 views

How does the supposed "Unified Architecture for NLP" from Collobert and Weston 2008 really works?

In this paper (here) they suppose a "unified architecture for NLP" with deep neural networks with multitask learning My problem is to understand the layered architecture in figure 1, see ...
15
votes
3answers
5k views

Modelling Unevenly Spaced Time Series

I have a continuous variable, sampled over a period of a year at irregular intervals. Some days have more than one observation per hour, while other periods have nothing for days. This makes it ...
5
votes
1answer
3k views

Neural Networks getting stuck at local optima

I'm training a NN with 8 features and 8000 training examples with a single output (0, 1) using the scipy.optimise CG algorithm and the results are somewhat inconsistent. The goal is to get the NN to ...
7
votes
5answers
661 views

Where to start on neural networks

First of all I know the question may be not suitable for the website but I'd really appreciate it if you just gave me some pointers. I'm a 16 years old programmer, I've had experience with many ...
26
votes
3answers
2k views

Why are NLP and Machine Learning communities interested in deep learning?

I hope you can help me, as I have some questions on this topic. I'm new in the field of deep learning, and while I did some tutorials, I can't relate or distinguish concepts from one another.
3
votes
1answer
68 views

What circumstances causes two different classifiers to classify data exactly like one another

Okay, here is the background: I am doing text mining, and my basic flow is like this: extract feature (n-gram), reduce feature count, score (tf-idf) and classify. for my own sake i am doing comparison ...
2
votes
0answers
67 views

What are some best papers on gradient descent for NN implementation? [closed]

I'm trying to implement GD for standard task of NN training :) The best papers for practioneer I've founded so far are: 1) "Efficient BackProp" by Yann LeCun et al. 2) "Stochastic Gradient Descent ...
11
votes
2answers
729 views

Neural net for server monitoring

I'm looking at pybrain for taking server monitor alarms and determining the root cause of a problem. I'm happy with training it using supervised learning and curating the training data sets. The data ...
7
votes
3answers
1k views

Forecasting Foreign Exchange with Neural Network - Lag in Prediction

I have a question regarding the use of neural network. I am currently working with R (neuralnet package) and I am facing the following issue. My testing and validation set are always late with respect ...
31
votes
4answers
24k views

Neural Network parse string data?

So, I'm just starting to learn how a neural network can operate to recognize patterns and categorize inputs, and I've seen how an artificial neural network can parse image data and categorize the ...
56
votes
3answers
23k views

How to fight underfitting in a deep neural net

When I started with artificial neural networks (NN) I thought I'd have to fight overfitting as the main problem. But in practice I can't even get my NN to pass the 20% error rate barrier. I can't even ...
6
votes
1answer
357 views

Trying to understand free-energy equations in a Karl Friston neuroscience article

I am trying to understand a neuroscience article: Friston, Karl J., et al. "Action and behavior: a free-energy formulation." Biological cybernetics 102.3 (2010): 227-260. (DOI 10.1007/s00422-010-0364-...
19
votes
2answers
6k views

How to choose the features for a neural network?

I know that there is no a clear answer for this question, but let's suppose that I have a huge neural network, with a lot of data and I want to add a new feature in input. The "best" way ...
149
votes
17answers
124k views

Best python library for neural networks

I'm using Neural Networks to solve different Machine learning problems. I'm using Python and pybrain but this library is almost discontinued. Are there other good alternatives in Python?
10
votes
2answers
2k views

Foreign exchange market forecasting with neural networks

I would like to use ANN to automate trading currencies, preferably USD/EUR or USD/GBP. I know this is hard and may not be straightforward. I have already read some papers and done some experiments but ...
9
votes
2answers
601 views

Any differences in regularisation in MLP between batch and individual updates?

I have just learned about regularisation as an approach to control over-fitting, and I would like to incorporate the idea into a simple implementation of backpropagation and Multilayer perceptron (MLP)...
2
votes
3answers
2k views

How to use neural networks with large and variable number of inputs?

I'm new to machine learning, but I have an interesting problem. I have a large sample of people and visited sites. Some people have indicated gender, age, and other parameters. Now I want to restore ...
26
votes
4answers
13k views

Word2Vec for Named Entity Recognition

I'm looking to use google's word2vec implementation to build a named entity recognition system. I've heard that recursive neural nets with back propagation through structure are well suited for named ...
10
votes
4answers
770 views

Gas consumption outliers detection - Neural network project. Bad results

I tried to detect outliers in the energy gas consumption of some dutch buildings, building a neural network model. I have very bad results, but I can't find the reason. I am not an expert so I would ...
110
votes
10answers
111k views

Choosing a learning rate

I'm currently working on implementing Stochastic Gradient Descent, SGD, for neural nets using back-propagation, and while I understand its purpose I have some ...
10
votes
2answers
2k views

Debugging Neural Networks

I've built an artificial neural network in python using the scipy.optimize.minimize (Conjugate gradient) optimization function. I've implemented gradient checking, double checked everything etc and I'...
8
votes
2answers
1k views

Multi layer back propagation Neural network for classification

Can someone explain me, how to classify a data like MNIST with MLBP-Neural network if I make more than one output (e.g 8), I mean if I just use one output I can easily classify the data, but if I use ...

1
75 76 77 78
79