Questions tagged [time-series]

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

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0answers
454 views

How to set LSTM for train on multiple time series on keras?

Greeting, everyone! I have $X = (x_1,x_2,...,x_n)$, and $Y = (y_1,y_2,...,y_n)$ where $x_i$ - is a time series, and $y_i$ - is the output time series for $x_i$. e.g. for $x_{ik}$ ($i$ - index of time ...
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2answers
56 views

Predicting the variable's score using predictive analytics

I am new to predictive analytics but I am good at programming (like Spark, R). I have 10 variables and I know their score's for over a long period of time. I want to know which variable will have ...
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140 views

How can I prepare my data from multiple time series sources for time series regression? [closed]

I have multiple sensors providing time series sources with slightly different time stamps and different sampling rates. For example I have a breathing rate feature from 1 sensor at 1 Hz, EKG from ...
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1answer
6k views

Predict multi-steps for Multi-Time series output with Keras

I have a dataset like the following one: Each column is a different numerical feature. Each row represents a timestamp. I want to create an LSTM model that can make prediction of the future time-...
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1answer
11k 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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0answers
288 views

Reformatting data for future time series prediction LSTM(Keras)

So I am following this notebook(at least for the data portion)and have a trained model. What I am trying to do is true future predictions as LSTM are capable of generating data for unseen time steps(...
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0answers
360 views

Anomaly detection in cooling process data without exact labels

I have a data set where I look at the cooling of a process. The starting temperature may vary between 580 and 180 degrees. I know that at some point the cooling system failed (see examples in the plot)...
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0answers
87 views

How to build a predictive model on Time series data [closed]

I have a time series data containing hotel occupancy rates from January 2014 to December 2017. I have run a forecasting model (Holtswinter in R). Now, I want to predict the significant external ...
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1answer
2k views

Difference between Time series clustering and Time series Segmentation

In the context of time series data mining, I have read about time series segmentation and time series clustering, but I couldn't differentiate between both. In case they are different, how these ...
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0answers
1k views

How to plot prediction intervals in seaborn tsplot?

I am plotting a group of time series plots with CI's in seaborn using tsplot: These were produced from 10 traces each: The confidence bars shown (99% confidence) appear to be the CI's for the mean. ...
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2answers
2k views

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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1answer
37 views

outlier detection in time serie without using windows [closed]

I would like to know if it's possible to detect outliers in a time-serie with an outlier score computed given the whole dataset and not given windows
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2answers
5k views

Why are RNN/LSTM preferred in time series analysis and not other NN?

I had recently a great discussion about the advantages of RNN/LSTM in time series analysis in comparison to other Neural Networks like MLP or CNN. The other side said, that: The NN just have to be ...
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2answers
4k views

Improving LSTM Time-series Predictions

I have been getting poor results on my time series predictions with a LSTM network. I'm looking for any ideas to improve the model. The above graph shows the True Data vs. Predictions. The True Data ...
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0answers
404 views

Ideas for using polynomial regression for multivariate time series prediction

I would like to predict next 12 months of employee count based on 3 or more years of data that includes salaries, profit and employee count. I have also interpolated monthly values for these three ...
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1answer
5k views

how to compare different sets of time series data

I am trying to do some anomaly detection between time#series using Python and sklearn (but other package suggestions are definitely welcome!). I have a set of 10 time-series; each time-series ...
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0answers
51 views

Classify people, predict event

Let's pretend we have a series of events, which have binary results $ y_1, \ldots, y_n $. For every event we have a number of people with more or less stable features $ f_1, \ldots, f_k $ (like sex ...
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1answer
2k views

RMSE in Weka Time Series Forecasting

I am using Weka Time Series Forecasting to forecast the trend of the topic NLP in 2018. For that I used ...
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1answer
201 views

LSTM with auxiliary data achieves abismal results [closed]

I have a fairly simple LSTM models that achieves ok results. I wanted to add auxiliary data as appeared in the keras docs. I added only one binary variable. I expected this model to be at least as ...
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1answer
66 views

What should be the training frequency of a rnn model for timeseries prediction? [closed]

If I use a rnn model for time series forecasting how frequently do I have to retrain the model.
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1answer
53 views

Features for blink detection in real-time single channel EEG [closed]

I am looking to detect blink events in real-time single channel EEG. Classification of a moving window of samples to determine whether a blink artifact exists requires feature extraction (except when ...
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1answer
55 views

How can I implement my own AR(p) simulation algorithm?

Recall that an AR(p) process can be defined as $$ X_t = \phi_1 X_{t-1} + \cdots + \phi_p X_{t-p} + Z_t $$ where $Z_t$ is I.I.D. white noise. I want to write an algorithm simulating these processes, ...
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1answer
460 views

How do I find a repeating pattern of unknown length and start within a string

Background: I am trying to do some analysis on our customer's around identifying early markers for debt delinquency. We bill customers on a weekly basis and payment patterns will differ between ...
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1answer
9k views

Basic Time Series Classification Examples [closed]

I've been using matlab until now to classify a large number of labelled time series I have. This has been relatively successful but I'd like to try using Tensorflow to apply a Deep Learning paradigm ...
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1answer
1k views

Machine learning algorithms for time series analysis [closed]

I am wondering which ML algoirthms (supervised) are commonly used for TS analysis. Which ones have used and found to be succesful for your projects?
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1answer
3k views

Does it make sense that datetime encodes one-hot-vector like one-hot-encoding or something else like

I'm new to machine learning and deep learning. I've wanted to solve time series problem, which has data every single second. Plus, I've been doing research on word2vector and time series data lately. ...
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1answer
1k views

What to give as predictors to predict future values?

I am new to machine learning techniques. I was going through few supervised machine learning model examples and i have doubt in predicting future values. I have daily time series dataset from ...
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2answers
144 views

Creating categorical variable, without knowing true categories (through binning time series data)?

I have a temperature dataset (data every 15 mins) to build a supervised classification/prediction algorithm, but only know one of the true classes (when data is nearly flatlining around 35deg) ...
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2answers
52 views

Privacy through moving averages?

I am considering the following hypothetical situation: I have a time series of data. In general, 'the public' should have access to features of this data. However, making the time series available ...
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1answer
255 views

Detect constant (zero-slope) sections in a noisy step function

I have data that has the shape of a step function, which is obstructed by noise. I would like to identify the sections with constant slope in it. The noise does not necessarily have 0 mean, and the ...
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4answers
10k views

Classify multivariate time series

I have a set of data composed of time series (8 points) with about 40 dimensions (so each time series is 8 by 40). The corresponding ouput (the possible outcomes for the categories ) is eitheir 0 or 1....
2
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0answers
716 views

How to scale data for LSTM autoencoder?

I am working on an LSTM autoencoder in keras. The aim here is to obtain a latent space representation for the time sequences which I intend to use for clustering. My input sequences (each feature) ...
4
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1answer
1k views

Combining Linear Regression and Time Series

Does anyone know of a predictive model that can combine the linear regression model and time series model? I have some data about some products. The data has two parts, some attributes about the ...
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0answers
137 views

Machine Learning: Repetitive Pattern recognition regardless of amplitude and frequency

I am trying to scope out an approach to learn to identify repetitive human body activity based on collected motion data and would like some advice on some challenges I identified. I determined a set ...
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0answers
201 views

Feature selection with many Time stamp data and Model classification

I’ve a data set with many Timestamp features like: Employee duty report time Employee duty release time Employee work start time Employee work end time etc. We currently have a Java application ...
2
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1answer
1k views

acf function shows error while fiiting time series

I am fitting a time series model in R. I plotted the time series to check for the pattern of it. It has 30625 observations. The observations are half hourly ...
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0answers
423 views

How to identify ARIMA model parameters

I am trying to build ARIMA model, I have 144 terms in my standardized time series, which represent residuals form original time series. This residuals, on which I would like to build ARIMA model, are ...
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0answers
93 views

Multivariate non-negative, discrete time series forecasting with neural networks

I have a data set obtained from the event log of a bunch of access points in a building. At the moment I am interested in forecasting, for each access point, the number of connected devices at each ...
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1answer
641 views

Classify Customers based on 2 features AND a Time series of events

I need help on what should be my next step in an algorithm I am designing. Due to NDAs, I can't disclose much, but I'll try to be generic and understandable. Basically, after several steps in the ...
1
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1answer
101 views

About training and cross validation on a time series problem

I am new to machine learning. I'm having a task of predicting whether a user will churn in March, given February feature data and the churn result. However, March data is leaked and now I'm assigned ...
2
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1answer
664 views

LSTM Validation MSE always lower than Train MSE

I am trying to train a LSTM network to forecast time steps further. I have a list of queries and the current question is based on one among them. The validation loss (using mse) is always lower than ...
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0answers
414 views

Spark fitting into Data Science Paradigm for timeseries data

I have seen Dataframe as new API on Spark2 instead of RDD.So I have following few question about the utility of Spark in terms of time series data. Is forecasting still limited to memory available in ...
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2answers
771 views

Predicting future airfare using past data

I have chosen the topic of "Predicting future airfare using past data" for my project and would love to get inputs on the best models to use. Data Set The data set consists of 6 months of time ...
1
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1answer
666 views

How to handle non-stationary data in online neural network based one-class classifier for anomaly detection?

I have developed online neural network based one-class classifier and also enabled it for forgetting mechanism. So, now online learning with forgetting mechanism is possible. But how to handle if data ...
2
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2answers
5k views

Multidimensional Dynamic Time Warping Implementation in Python - confirm?

I believe that I implemented MDTW in python here but I don't know if I did it correctly. The results seem intuitive. Can someone look at this code and tell me if you see anything wrong? A lot of the ...
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1answer
357 views

Long term time series forecasts with small dataset

I have a small dataset which has timestamp and temperature values for 6 months(I.e. one temperature value per day). I would like to forecast 2-3 months of temperature. I would like to know, what kind ...
2
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0answers
40 views

How to properly implement a CausalImpact on a time series

I have a time series with the percentage of the subscriber based on the total users in my platform. Let's say I did an event that could, potentially, affected the figures. I could run a CausalImpact ...
4
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0answers
3k views

Kalman filter for time series prediction

I have the information about the behaviour of 400 users across period of 1 months (30 days). Across those 30 days I measure 4 different information (let's call it A,B,C and D), hence I have a total of ...
2
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1answer
279 views

RNN unable to classify time series

I have 400 time series of length 50. 200 of them have values between 1-10 and are considered of type A. The rest 200 have values 1-10 with the exception that 3 from the total of 50 data points have ...
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1answer
215 views

Classifying time series data that overlap

I am working with Time-Series Data that has to be classified into two classes (Blue and Red) or at least Classify the data as one class (Red), I'm unable to come up with features that distinctly ...

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