Questions tagged [time-series]

For questions related to time series analysis or forecasting in the context of AI and, in particular, ML.

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3
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2answers
61 views

Image vs Non-Image Data in CNN

When using CNN on non-image(times series) data prediction, what are some constraints or things to look out for as compared to image data? To be more precise, I ...
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0answers
14 views

Deep Learning on time series tabular data

In this new book release, at the top of page 51 the authors mention that to do deep learning on time series tabular data the developer should structure the tensors such that the channels represent the ...
3
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1answer
24 views

Can non-sequential deep learning models outperform sequential models in time series forecasting?

Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? I know this question is not very specific, but I experienced this when ...
2
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1answer
27 views

Feature extraction timeseries, model compatibility

I've got a timeseries with sensor data (e.g. accelerometer and gyroscope). I now want to extract the activity out of it (e.g. walking, standing, driving, ...). I Followed this Jupyter Notebook. But ...
5
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1answer
230 views

What is the “semantic level”?

I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al. In this paper, they use several times the expression "semantic ...
2
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1answer
39 views

ValueError: Error when checking target: expected dense_3 to have shape (1,) but got array with shape (2,)

I am trying to build a CNN model on Keras. The data has a dimension of 921 rows × 10000 columns. Here is the code: ...
2
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0answers
23 views

Choosing neural network output for prediction (regression) of a dynamical system

I’m trying to train a neural network to approximate the output of a dynamical system $dy/dt=f\left(y(t), u(t) \right)$, namely, given $y(0)$ and $u(t_i), i=1,2...N$ I want the network to predict $y(...
1
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1answer
42 views

How can I test my trained network on the next unavailable hour?

I have data of 695 hours. I use the first 694 hours to train the network and I use 695th hour to validate it. Now my goal is to predict the next hour. How I can use my trained network to predict the ...
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0answers
13 views

What's the correct approach to standardise data from a time-series used for LSTM neural network predictions?

This question discusses the same model mentioned in Why is the value range of my LSTM model's prediction different from my test labels? Repeating the main points: I am using LSTM to do time-...
1
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1answer
46 views

Is it possible to use the GPT-2 model for time-series data prediction?

Is it possible and how trivial (or not) might it be (if possible) to retrain GPT-2 on time-series data instead of text?
3
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2answers
132 views

What kind of neural network architecture is suitable for variable length block-like time series data?

I'm not sure what this type of data is called, so I will give an example of the type of data I am working with: A city records its inflow and outflow of different types of vehicles every hour. More ...
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0answers
7 views

Looking for the right type of 1D-Convolution that only considers one column/attribute

My input has the shape of n rows (time steps) and m columns (attributes). I want to train a convolutional neural network on it to predict a class. I am currently using 1D-Convolutions. I got a good ...
2
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0answers
31 views

Are there any ways to model markov chains from time series data?

I want to make a thing that produces a stochastic process from time series data. The time series data is recorded every hour over the year, which means 24-hour of patterns exist for 365 days. What I ...
2
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2answers
41 views

Conferences for Human Activity Recognition

What are some conferences for publishing papers on Deep Learning for Human Activity recognition? Do any of the major conferences have specific tracks for Human Activity Recognition?
2
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0answers
42 views

Spike detection in time series using Artificial Neural Networks

I'm quite new in ANNs. I intend to use ANNs for predicting spike points in time series right before they happen. I've already used LSTM for another scenario, and I know that they can be used in ...
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1answer
55 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
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0answers
38 views

What are the possible neural network architecture for linear regression or time series regression?

I started modeling a linear regression problem using dense layers (layers.dense), which works fine. I am really excited, and now I am trying to model a time series linear regression problem using CNN, ...
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0answers
34 views

Is it possible to use adversarial training to learn invariant features?

Given a set of time series data that are generated from different sites where all sites are investigating the same objective but with slightly different protocols. Is it possible to use adversarial ...
1
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1answer
34 views

Can HMM, MRF, or CRF be used to classify the state of a single observation, not the entire observation sequence?

I learn that the Viterbi algorithm used for Hidden Markov Model (HMM) can classify a sequence of hidden states from the corresponding observations; Markov Random Field (MRF) and Conditional Random ...
2
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1answer
74 views

LSTM Architecture

There is plenty of literature describing LSTMs in a lot of detail and how to use them for multi-variate or uni-variate forecasting problems. What I couldn't find though, is any papers or discussions ...
1
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1answer
50 views

Train and Test Accuracy of GRU network not increasing after 2nd epoch

So I´m currently implementing my first neural network using GRUs as a model and Keras as an implementation since it´s pretty highlevel. My problem is about the classification of 8 hour long timeseries ...
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0answers
7 views

Is there anyone who tried to discretize a continuous feature using the FDIC method(Frequency Dynamic Interval Class) ? (seems a great method)

I want to discretize a continuous attribute, I applied a lot of methods but it's clear that i'm losing information at each time, until I found the FDIC method wich seems great but I couldn't ...
2
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2answers
83 views

Why is it harder to achieve good results using neural network based algorithms for multi step time series forecasting?

There are different kinds of machine learning algorithms, both univariate and multivariate, that are used for time series forecasting: for example ARIMA, VAR or AR. Why is it harder (compared to ...