Questions tagged [time-series]

Time series are data observed over time (either in continuous time or at discrete time periods).

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3answers
2k views

which neural network topology to learn correlations between time series?

I have two (or more in principle) 1xN time series, and I would like to train a NN to predict the next value of both. I can arrange them as a 2xN matrix and feed a window from this matrix as input to ...
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2answers
257 views

Time series data: How I measure influence of new product sales on existing product sales (statistically)?

Here my goal is… Find Product 5 (New Product) is really influencing other product sales (product 1 to 4) or not? If it is influencing other product sales, how much? New to R and tried several ...
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3answers
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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 ...
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1answer
8k views

Multiple output for multi step ahead prediction using LSTM with keras

I am new to deep learning and LSTM (with keras). I am trying to solve a multi-step ahead time series prediction. I have 3 time series: A, B and C and I want to predict the values of C. I am training ...
7
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2answers
982 views

Time Series Machine Learning Feature Selection Problem

I have to solve a time series model that can take one of two shapes. It can probably take more but here are the two I'm going to ask about. If you have other ideas they are of course welcome. First ...
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2answers
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Why should I care about seasonal data when I forecast?

I have a timeseries with hourly gas consumption. I want to use ARMA/ARIMA to forecast the consumption on the next hour, basing on the previous. Why should I analyze/find the seasonality (with Seasonal ...
6
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1answer
2k views

What is the largest public wearable accelerometer dataset?

I'm looking for public datasets of people wearing a device with an accelerometer (and potentially other sensors eg gyroscope or magnetometer). What are some of the largest available datasets like ...
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1answer
5k views

How to use survival analysis for predictive maintenance for time series data?

So, I have a dataset with daily operating conditions for different machines and a flag saying if it failed or not. Here is a snapshot of the data. How can I use survival analysis or any other ...
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3answers
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How can Time Series Analysis be done with Categorical Variables

Most of the time series analysis tutorials/textbooks I've read about, be they for univariate or multivariate time series data, usually deal with continuous numerical variables. I currently have a ...
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3answers
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Multivariate Time series analysis: When is a CNN vs. LSTM appropriate?

I have multiple features in a time series and want to predict the values of the same features for the next time step. I have already trained an LSTM which is working okay, but takes a bit long to ...
6
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1answer
6k views

Is it necessary to perform rolling-window on LSTMs?

Let's say I have a set of n time-series with sequence length 8 [[a,b,c,d,e,f,g,h],[f,e,g,r,g,h,e,a],[a,e,r,a,k,e,l,i],...,[e,r,q,g,l,r,p,q]] And let's define the input that LSTM expects as a ...
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4answers
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Time series forecasting dilemma. Could feature engineering overcome time dependency?

I keep reading articles about time series forecasting. They all start from the same assumption: time series forecasting can't be treated as a regression/classification problem. It is time dependent, ...
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2answers
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Alternative distance to Dynamic Time Warping

I am performing a comparison among time series by using Dynamic Time Warping (DTW). However, it is not a real distance, but a distance-like quantity, since it doesn't assure the triangle inequality to ...
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2answers
926 views

Anomaly detection in time series

The use case : Everyday, we have metrics that are established daily to check that our systems are doing fine. From time to times, bugs occur in the workflow building these metrics, and I have to ...
6
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1answer
3k views

Similarity measure for multivariate time series with heterogeous length and content

I am interested in clustering multivariate N time series of T'values' each(different lengths) using python. Each variable have many trends and values which are simultaneously numeric and nominal. A ...
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2answers
2k views

Recurring events - finding in a time series

I have an event dataset from which I would like to detect recurring events (i.e: weekly, bi-weekly, monthly). The dataset contains: Timestamp (date) Event type which can get any value (e.g: ...
6
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1answer
162 views

How to do this complicated data extrapolation, prediction modeling?

I have some very complicated data about some movie sales online, first for each data entry, I have a key which is a combination of five keys, which are territory, day, etc, and then, for each key I ...
6
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2answers
489 views

Looking for algebras designed to transform time series

I am looking for information on (formal) algebraic systems that can be used to transform time-series - in either a practical or academic context. I hope that there exists (at least one) small, ...
6
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1answer
293 views

Classification of a time series data

I have 5 different classes in which I want to classify some data points. I'm using RNN with Echo-state networks (Reservoir computing). Normally, a straightforward method consists of computing the ...
6
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1answer
250 views

Estimating the battery capacity using current power consumption and battery percentage

I want to estimate the current maximum capacity (in kWh) having the current power consumption (in kWh) and the state of charge of the battery (in %) available in a time series. I do not have a full ...
6
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1answer
3k views

Choosing a window size for DTW

I have time series data from mobile sensors for different motions such as walking, pushups, dumbellifts, rowing and so on. All these motions have different length of time series. For classifying them ...
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3answers
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How do you compare term counts between two different periods, with different underlying corpus sizes, without bias?

I'll set the question up with an example. You are analysing news coverage text data from 2014, and find that a term appears less often in the third quarter of 2014 than the final quarter (let's ...
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3answers
861 views

Quasi-categorical variables - any ideas?

Let's say I'm trying to predict a person's electricity consumption, using the time of day as a predictor (hours 00-23), and further assume I have a hefty but finite amount of historical measurements. ...
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5answers
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Additive vs Multiplicative model in Time Series Data

The above time series plot is a daily closing stock index of a company. I want to know which model between additive and multiplicative best suits the above data. I know what the two models are, but i ...
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2answers
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RNN time-series predictions with multiple features containing non-numeric features and numeric features?

The question RNN's with multiple features is ambiguous and not explicitly in differentiating different features. I want to understand how to use RNN to predict time-series with multiple features ...
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3answers
838 views

Deploying an LSTM Model

I have trained and validated my LSTM and I would like to deploy it. So, I know that we can save and load the Sequential object of Keras (I am working with Keras as you can guess). I thus implemented a ...
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2answers
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How can I use variable length inputs to train a regression model?

I'm working predicting a value $y \in \mathbb{R}$ from the value of $x_{n+1}$, where $n$ is the number of samples ($x_{i \in [1,n]}$) used for training. Each training sample $x_{i}$ is a time series ...
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2answers
1k views

Time series prediction

I am trying to predict a time serie from another one. My approach is based on a moving windows. I predict the output value of the serie from the following features: the previous value and the 6 past ...
5
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1answer
939 views

The use of Keras self-attention module

This question calls people to share their personal experiences with keras_self_attention module. I also summarized the problems I encountered and the solutions I ...
5
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3answers
8k views

LSTM for time series - which window size to use

I have a LSTM based network which inputs a n-sized sequence of length (n x 300) and outputs the next single step (1 x 300). The "raw" data consists of a few thousand semi-processed sequences of ...
5
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2answers
12k views

Sequence data vs time series data

What is the difference between sequence data and time series data? My understanding is that sequence data is any data where the order matters and time series is a special type of sequence data ...
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1answer
4k views

How to transform raw data to fixed-frequency time series?

How to transform raw data to fixed-frequency time series? For example I have the following raw data in DataFrame ...
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2answers
3k views

Tool for labeling audio

I have few thousand audio signals to label into 2 different classes and save them to numpy array for further training of models. MATLAB recently released ...
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2answers
9k views

How would I apply anomaly detection to time series data in LSTM?

I am using a LSTM RNN in Python and have successfully completed the prediction phase. My ultimate goal is anomaly detection. I'm hoping to have something like what you could see on Facebook Prophet, ...
5
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2answers
400 views

Predicting with multiple time series

Say you had a set of users, tens of thousands. You have time series of each of their behaviors using this app. How might you use these time series to predict future behavior of new users? The ...
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2answers
7k views

Time series forecasting with RNN(stateful LSTM) produces constant values

I have a time series daily data for about 6 years(1.8k data points). I am trying to forecast the next t+30 values, Train data independent matrix (X)=Sequences of previous 30 day values Train (Y)=The ...
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2answers
8k views

Using RNN (LSTM) for predicting one future value of a time series

I have been reading several papers, articles and blog posts about RNNs (LSTM specifically) and how we can use them to do time series prediction. In almost all examples and codes I have found, the ...
5
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2answers
889 views

Statistical distances for time series of distributions

I am interested in clustering $N$ time series of $T$ 'values' each. These values are distributions (which can be represented by their cumulative distribution functions (cdf), or their probability ...
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1answer
5k views

Is there an R tutorial of using LSTM for multivariate time series forecasting?

There is a great blog post about how to use keras stateful LSTM in R to forecast sunspots. I applied it to financial ts data ...
5
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1answer
4k views

When should you balance a time series dataset?

I'm training a machine learning algorithm to classify up/down trends in a time series and I'm using an imbalanced feature set. It seems necessary to balance the data since the algorithm could learn a ...
5
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1answer
3k views

Batching in Recurrent Neural Networks (RNNs) when there is only a single instance per time step?

I have scoured the internet and books, but everything seems to use num_steps and batch_size or similar terms interchangeably and ...
5
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1answer
3k views

Anomaly detection for transaction data

I have transaction details for credit data (bank transfers, peer to peer transfers, etc). Currently, I have one year worth of data which I cannot properly classify. I'm looking for input and ...
5
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1answer
707 views

Error analysis for better accuracy

I have historic error of time series. I want to analyze error series to improve forecast series. Are there any methods to do this?
5
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1answer
843 views

Do I need to engineer lagged features when creating an LSTM for time series forecasting?

Long short-term memory networks are fairly complicated and I haven't completely wrapped my head around them. It seems to me like the big gain in LSTMs for time series forecasting is the lacking ...
5
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1answer
1k views

Financial Time Series data normalization

I'm using Keras in R to predict financial time series. It's easy to normalize price, simply compute returns or log returns, usually it's enough. I want to use Goldman Sachs Financial Conditions Index ...
5
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1answer
3k views

Recurrent Neural Network on Panel Data

There are 2 parts to this question. Suppose we are looking at sales $S$ of a product across $> 1000$ stores where a it sells. For each of these $1000$ stores we have 24 months recorded data. We ...
5
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2answers
801 views

Time series classification

I am looking at time series security attack data where a given IP can either be labeled as (1) attack or (0) no attack. In total we will have thousands of IPs and roughly an equal number of attacks ...
5
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1answer
74 views

Relation mining of multivariant categorical timeseries without excluding the temporal nature

To all: I have been wracking my brain at this for a while and thought maybe someone here would know of a package or algorithm to handle the following: I have nominal multivariant timeseries that ...
5
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1answer
164 views

which algorithms can be used to extrapolate non-linear data?

I have a dataset, where target value changes in time in following way: I need to predict target value for upcoming month, however I struggle to find a method to extrapolate the function that defines ...
5
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1answer
90 views

Influence of trend on (supposedly) correlated time series

TL;DR: What is the impact of a linear trend on the correlation between time series that are (most likely) not spuriously correlated? I'm currently trying to reconstruct/cross-validate an analysis ...

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