All Questions
Tagged with neural-networks time-series
419 questions
3
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1
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2k
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Conditional restricted Boltzmann machines on a time series dataset
Preamble of the problem
I am currently trying to apply Conditional Restricted Boltzmann Machines on a time series dataset problem, in particular, the dataset constitutes of ...
- 379
55
votes
5
answers
41k
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Using deep learning for time series prediction
I'm new in area of deep learning and for me first step was to read interesting articles from deeplearning.net site. In papers about deep learning, Hinton and others mostly talk about applying it to ...
- 651
2
votes
1
answer
203
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Online learning to maximize profit
I have a software which takes input as investment and gives the output as return on a particular stock. Now profit metric $x_i$ is defined as the ratio of return $g_i$ to maximum possible return $g_{...
- 23
1
vote
1
answer
124
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Predict near future data from another correlated data source that varies quicker
I'm trying to figure out a way to predict the evolution of some data in the near future by using another data source that is correlated to that one but that varies quicker.
For instance, I have the ...
- 121
7
votes
1
answer
3k
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Combine several softmax output probabilities
I would like to combine the outputs of five neural networks, each with a softmax output layer of three classes each. A typical, example output is shown below:-
where Figure 1 is the output of model 1,...
- 4,869
8
votes
2
answers
16k
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Classification in time series: SVMs, Neural Networks, Random Forests or non parametric models
My dataset is made of a label, $y_{t}$, which is the dependent variable, and about 20 columns of independent numeric variables, $X_{t}$, $t=1,2,...,T$.
These samples are time series and my goal is to ...
- 637
9
votes
2
answers
35k
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Example of time series prediction using neural networks in R
Anyone's got a quick short educational example how to use neural networks (nnet in R for example) for the purpose of prediction?
Here is an example, in R, of a ...
- 399
3
votes
1
answer
2k
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Cross-validation with neural networks yielding worse results than a standard neural network
Summary: when using a 10-fold cross-validation procedure where each training set is used to generate N bootstrap samples for processing with NNs. How do I provide my NN with correct sequence and ...
- 233
0
votes
1
answer
100
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Using ANN in time series with limited observations
I'm trying to predict weekly market shares over time with a small data set (190 examples and 4 inputs).
My questions are the following:
Is there a particular technique for small number of ...
- 11
7
votes
2
answers
7k
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Predicting time series with NNs: should the data set be shuffled?
Suppose I'm trying to predict time series with a neural network. The data set is created from a single column of temporal data, where the inputs of each pattern are ...
- 708
1
vote
2
answers
898
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How to select input values for neural networks?
I'm new to forecasting using neural networks. I have decided to use feedforward backpropagation algorithm. What are the input values if I have past data and what is the technique to select input ...
- 375
6
votes
4
answers
7k
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Time series analysis with neural networks
I'm new to neural networks and machine learning and I was wondering how you use time series data to set the weights of a regular FNN, and how you use the ending weights to forecast the time series. In ...
- 61
2
votes
0
answers
1k
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Using autocorrelation plots to choose the number of inputs for a neural network predicting time series
A neural network applied to time series needs to have the number of input nodes defined. Each input is applied to a time point previous to the current point being predicted. If $D$ is the number of ...
- 1,705
8
votes
3
answers
2k
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Multilayer neural networks for multivariate temporal data
I'm looking for a way to model and extract features from multivariate temporal data (e.g., multi-channel audio recordings).
I'm specifically interested in deep learning methods such as RBM, sparse ...
- 1,626
8
votes
3
answers
8k
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Recurrent neural networks in R
I've heard a bit about using neural networks to forecast time series, specifically recurrent neural networks.
I was wondering, is there a recurrent neural network package for R? I can't seem to find ...
- 24.4k
8
votes
3
answers
3k
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k-fold CV of forecasting financial time series -- is performance on last fold more relevant?
I am working on an ANN-based forecasting model for a financial time series. I'm using 5-fold cross-validation and the average performance is so so. Performance on the last fold (the iteration where ...
- 83
92
votes
1
answer
88k
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How to apply Neural Network to time series forecasting?
I'm new to machine learning, and I have been trying to figure out how to apply neural network to time series forecasting. I have found resource related to my query, but I seem to still be a bit lost. ...
- 1,055
16
votes
2
answers
8k
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Getting started with neural networks for forecasting
I need some resources to get started on using neural networks for time series forecasting. I am wary of implementing some paper and then finding out that they have greatly over stated the potential of ...
user4280
70
votes
3
answers
48k
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Proper way of using recurrent neural network for time series analysis
Recurrent neural networks differ from "regular" ones by the fact that they have a "memory" layer. Due to this layer, recurrent NN's are supposed to be useful in time series modelling. However, I'm not ...
- 2,767