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Questions tagged [time-series]

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

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White noise seasonality

Is the above graph a white noise? I'm confused by the spikes at certain places. The above plot has been obtained after doing a first order differencing on a time series. How can I justify whether ...
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predictive clustering trees in Python?

I am faced with a time series forecasting cold-start problem, specifically I am forecasting energy consumption of businesses where historic consumption data is available only for training but not new ...
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7 views

Train Keras LSTM for sequential data, where the target values for every element are given, except for the last one?

I am currently working on a data set with sequences of trips from certain people. These trips take place from one cluster to another. The starting-cluster of a trip does not always equal to the ...
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1answer
19 views

How to encode a time series as an image to feed it into CNN?

I want to try CNN in the task of stock chart pattern recognition. I suspect that feeding a line chart won't work because the image will have a lot of empty pixels. What time series encoding options ...
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Compare noise level of time series from different sources

I have multiple time series from different sources and they have different scale. For example - ...
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24 views

GANs for Stock Market Prediction [closed]

I need help in implementing a GAN for predicting stock market prices. I want to know, how can I implement this using Keras framework and how would I go in structuring the whole architecture. I will ...
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1answer
16 views

What are the key differences between a MLP with lagged features and a RNN

I've been working with MLP's for a while. Whenever I assumed that the past values of a feature might be useful for predicting the future values of Y, I would just create a new column in my data frame ...
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38 views

Model for time series analysis

I'm new to data analysis and ML in general. I'm working with some friends on this problem: We're trying to predict when a component of a machine will stop working properly so the client can change it ...
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18 views

Predicting stock market index values using individual stocks

I'm trying to predict the market trend (i.e. predict the value of a stock market index, e.g. S&P 500) using the stocks in the index. My data-set is as follows: ...
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1answer
17 views

Using a loop to predict longer vectors with a LSTM

I have a model based on LSTMs that can predict a vector output based on a vector input. I can't increase the size of the output because : I would need a larger network to obtain good results It would ...
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1answer
49 views

Time Series - Models seem to not learn

I am doing my undergrad Dissertation on time series prediction, and use various models (linear /ridge regression, AR(2), Random Forest, SVR, and 4 variations of Neural Networks) to try and 'predict' (...
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1answer
17 views

How to forecast time series analysis for more then one dependent variables?

I have three datasets as: Dataset_1= column name as ID, Date, counter_id Dataset_2= column name as ID, no. of tickets sold ...
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1answer
75 views

How to feed a table per timestamp to LSTM neural network?

I have a time-series dataframe like this ...
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Is the mean shift algorithm adapted to my problem?

I'm currently building a model that can detect abnormalities in a timeserie. First, we predict the next steps and then we compare the prediction with what we measure in real time. We want to see if ...
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2answers
29 views

Labeling classes conditionally

I am working with a time series predicting whether web traffic will increase or decrease each day compared to the previous day for a given user. Initially I used binary classes: labeled 1 for next ...
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1answer
16 views

How to figure out if the problem is time series Forecasting or not?

Recently I have encountered a time-series based, where I have a dataset which contains data for call-centers performance. The dataset contains information about the number of calls made by customers ...
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Comparing simulated Lightcurve with measured lightcurve of satellites

With python I want to compare a simulated light curve with the real light curve. It should be mentioned that the measured data contain gaps and outliers and the time steps are not constant. The model, ...
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1answer
23 views

Classifying ultrasound videos with a small dataset

I have a small dataset of ~300 ultrasound clips, about evenly divided between 3 classes. Due to the nature of the data (medical) it's difficult to get more. I need to train a model (or an ensemble) ...
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1answer
21 views

Predict how many days late or early someone will finish their work

So I have a set of deadlines and people, with a database of when those people finished their previous work and how much after the deadline it was, as well as when the work was given. The work itself ...
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1answer
41 views

Training a LSTM on a time serie containing multiple inputs for each timestep

I am trying to train a LSTM in order to use it for forecasting : the problem is basically a multivariate multi-steps time series problem. It is simply an experiment to see how statistical models (...
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1answer
27 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 ...
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1answer
40 views

Determining if time series follows a pattern

I was wondering if anyone had any idea how to solve this problem. So basically I have a dataset where some person approximately comes at some regular interval and I don't know what that interval is. ...
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28 views

Time-series forecasting

Here is the data: ...
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1answer
56 views

How to measaure the similarity between two series?

I'm confused about how to measure the similarity between two time series with the same length. For example, both time series are 2 hours in length and every 5 minutes a point. I really want to know ...
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0answers
52 views

Training data : forecasted or actual?

I am working on a time series prediction problem. I am using keras models for machine learning. For this prediction, weather variables are used as input. They can be of two types: forecasted and ...
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What's the difference between ELM and NNAR?

I'm working with time series forecasting using the two techniques that involve neural networks, the Extreme Learning Machine and the Autoregressive Neural Network. Reading the two methodologies, the ...
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1answer
40 views

How to get vector representations(or embeddings) of time series?

Even if a time series is constructed up of numbers only, finding abstract fixed-dim vector representation would be interesting for classification/clustering purposes. As we can learn & find ...
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Adding context in a sequence to sequence problem

The encoder of a seq2seq model is meant to generate a conditioning context for the decoder, as mentioned here A RNN layer (or stack thereof) acts as "encoder": it processes the input sequence and ...
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Predicting when features are time-dependent

How to predict data with time-dependent features? For example, I have to predict the result of a Mortal Combat game: ...
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2answers
34 views

Random Forests Feature Selection on Time Series Data

I have a dataset with N amount of features, each one with 500 instances in time. Let's say that I have for example, the features x, y, v_x, v_y, a_x, a_y, j_x, j_y....
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1answer
27 views

Calculating Feature Importance of Time Series Data

I am new to time-series modeling, and I was wondering what the standard way of quantifying feature importances are in a time-series setting? What types of models allow for the greatest interpretation ...
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8 views

Activity Recognition of non periodic activites

The data consits of single time series instances of a complex activity that can be divided into single non-periodic activities. The data was collected using mobile phones, holding information about ...
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1answer
25 views

How to approach clustering of time-series with a single variable

Let me preface this by saying that I'm a complete beginner to R and data science in general, so my apologies if this is a rather trivial question. I do have a rough idea of what I would like to ...
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1answer
19 views

Correlation between Time Series Indicators ( Stock Prices )

I am new to time series analysis and I am currently tackling a stock market prediction problem. I have a set of market indicators (such as Bollinger Bands, ADX etc) which are derived from the time ...
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0answers
46 views

99% on the first epoch

I am working with time-series data and I am trying to classify the Fault happening in the system. The problem is no matter what I try so far, I get 99.79 validation accuracy on the very first epoch. ...
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0answers
53 views

How to model non-linear demand function?

I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. However, it seems to be ...
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1answer
54 views

Unsupervised learning for anomaly detection

I've started working on an anomaly detection in Python. My dataset is a time series one. The data is being collected by some sensors which record and collect data on semiconductor making machines. ...
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binary classification for time series data

I am a new to data science and I really appreciate any feedback on this problem. I have a dataset with 450 subjects. A binary response (yes/no) is measured every week on each subject for a total of ...
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1answer
66 views

Binary classification with time-series features

I have the following time-series features: Diastolic Blood Pressure, Systolic Blood Pressure, Heart Rate, RR variability and Arterial Blood Pressure. Each of these clinical parameters was measured for ...
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1answer
37 views

Algorithm suggestion for anomaly detection in multivariate time series data

I have time series data containing user actions at certain time intervals eg ...
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0answers
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Extracting disaggregated time series from an aggregate time series

I've got $N = 5000$ individual time series representing hourly electricity demand from $N$ households. I also know whether each house has electric heating or not. Assume there are $N^1$ houses with ...
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1answer
27 views

Model for classifying time-series data with distinct features?

I've heard about time-series classification being done with TCN's and CNN's combined with LSTM's very often, citing that CNN's would provide insight both forward and in the past since you already have ...
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Fitting model to differenced time series

I have a time series on daily stock price of company(2013 data points).I took a first order difference and the following acf and pacf plots of the differenced series were obtained. However, I am ...
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1answer
24 views

Books on time series and sequence classification

Though I have been using traditional machine learning algorithms (Regression and Classification) , I have no experience of using Time series and would like to understand what is time series and ...
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1answer
48 views

One-Dimensional Convolutional Neural Network

Can someone explain how 'One-Dimensional Convolutional Neural Network' works. I do understand the 2-D for image but for 1-D how is the filer created. is it fixed 1-D filter within a specific time ...
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1answer
22 views

Revenue Projection

Given that we have Monthly revenue data for pass 3 years (36 rows of revenue) We have other data including economic indicators, industry indicators as well (other columns in the 36 rows) ...
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1answer
30 views

How to estimate the not available observation in time series data?

Suppose, I have a 30 seconds time-step observations of sports data, in some of the intervals the game was partially/fully stopped. I'm trying to prep the data for a time series analysis. Is it ...
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1answer
30 views

Which different visualizations to make for time series analysis?

I hope you're doing great. I have recently started working on a time series project and I have just finished preparing my data and calculating trends (daily, weekly, yearly) and I wonder what are the ...
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0answers
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How to label smart meter/plug data (time series)? [closed]

I would like to label smart plug data recorded in different household appliances so that I can train a machine to recognize for example when the oven is turned on. I am new to this topic and I am ...
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0answers
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Can I have multiple (a sequence of) predicted values as the output of a neural network model?

I have a multi-dimensional time series data, and I want to use these data to do a time-series prediction. That is, the target(ground truth) of the training data is in a time series format instead of ...