Questions tagged [time-series]

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

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3k views

One-hot encode multi-class multi-label sequences

Suppose I want to build a timeseries where each timestep is represented by a categorical array: the encoded sequences look like [[2, 0, 5],[3, 1, 4],..] and each ...
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2answers
970 views

LSTM vs ARIMA for demand prediction

I'm new to the field of time series prediction. I'm looking for a demand prediction model to predict when the product will be sold out from the online supermarket (when the supply is known in advance)...
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VAR model ValueError: x already contains a constant

I'm using VAR model for multivariate time series. The structure is that although each variable is a linear function of past lags of itself and past lags of the other variables, one and/or two of the ...
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1answer
1k views

Multivariate Time-Series forecasting using LSTM

I have a dataset of hourly measures of pollution('Sample_Measurement) and weather condition. If I want to predict the pollution level of the current hour using the weather and pollution data of the ...
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1answer
71 views

Evaluating the result of topic modeling in a way that time matters

I have run different topic modeling approach on my data(its clinical data related to Cognitive impairment diseases. we are going to process what thing is important that make it develop to more harsh ...
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1answer
3k views

LSTM for time series forecasting with H20.ai

I want to implement a time-series prediction model using LSTMs like the one mentioned here: https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/ The ...
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1answer
472 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 ...
3
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1answer
762 views

ARIMAX v. ARX Time Series Modeling

I need to build a time series model with explanatory variables, and ARIMAX seems to be the one that comes up most frequently in practice, based on my survey of related work. I know ARX solves a ...
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2answers
153 views

Time-series multi-step generalization from single step model

I have built a generic stacked lstm model of the form: ...
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1answer
299 views

ARIMA training super slow

I am fitting ARIMA model (from statsmodels) on 20 000 elements dataset on a 24 CPU 200+GB RAM cloud server for over 24 hours now. It loads all the CPU's. But It takes so long... Is it how it works or ...
3
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1answer
360 views

What is the meaning of each element in input_shape of Conv1D in Keras?

I have a time-series data for 3 classes (each class is 35 second) as I extract each 1 second for 95 feature extracting so my final data has shape (105,95) (rows for time and column for feature). I am ...
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49 views

Time Series Clustering

The thing that I am trying to do is the time series shapes classification. Basically the problem is as following: Let's say I have some time series and my goal is to have an algorithm that "finds" ...
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1answer
59 views
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How can I use time stamps for classification?

My data consists of entries when an event is True, namely, when a train crossing is down. So I will have entries within a day like so (just examples): ...
3
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1answer
98 views

Terminology - regression with one output and multiple output variables

I am trying to predict the response when the input is represented by Fourier transform. These form the features and are typically represented as a vector, $x_1,x_2,...,x_d$ where $d$ is the length of ...
3
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1answer
215 views

How to correctly set a target for a time series based model?

I need help determining the best way to go about creating the target variable for a machine learning model that is trading a financial instrument (stocks, foreign currencies, crpyto, etc). Below is ...
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2answers
205 views

Time Series data: How to convert it in a streaming data?

I have a time series data which is available in offline csv format. I am using this data to create anomaly detection model. Although I could create this model to predict anomalies in this dataset, I ...
3
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1answer
69 views

Next year forecasting with monthly data from many, correlated, non-monotonic trends

I have trend data from many health departments in a local territory (eg. cardiology, orthopedics, etc...). These trends represent health service (visits, diagnostic, admissions) production, service ...
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1answer
539 views

How to Setup Multivariate Time Series Dataset for Classification

First post on StackExchange. I’m fairly new to ML, with about 1 year of experience so please pardon any ignorance or misuse of terms. I have a multivariate time series dataset where I would like to ...
3
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1answer
116 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' (...
3
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1answer
86 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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2answers
105 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. ...
3
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1answer
52 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 ...
3
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2answers
473 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. ...
3
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1answer
104 views

How can i find trend time for my articles?

our article is time-based, that means is my article search more in a specific time. as you can see in under chart this article search more in specific period time. if my dataset looks like this(it ...
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Are RNN or LSTM appropriate Neural Networks approaches for multivariate time-series regression?

Dear Data Science community, For a small project, I've started working on Neural networks as a regression tool, but I am still confused about possibilities of some variants. Here's what I am aiming ...
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2answers
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what happens to the depth channels when convolved by multiple filters in a cnn (keras, tensorflow)

I have a $15$-channel time series that I want to convolve using a $1$d CNN ($1\times n$ time-steps kernel). Now, let's say I want to have, as my first layer, $16$ filters. This would imply to my mind ...
3
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1answer
40 views

Adding more emphasis on most recent data in CNNs

I am using a CNN for multivariate time series analysis. The input size is (batch_size, 500, 30) i.e 30 variables and 500 time steps. I would like to put more ...
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2answers
6k views

Does this encoder-decoder LSTM make sense for time series sequence to sequence?

TASK given $\vec x = [x_{t=-3}, x_{t=-2}, x_{t=-1}, x_{t=0}]$ predict $\vec y = [x_{t=1}, x_{t=2}]$ Whith an LSTM encoder-decoder (seq2seq) MODEL NOTE: the ? symbol in the shape of the tensors refers ...
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344 views

Time series binary classificaiton with labelling issues

My situation is quite complicated so I will give a similar example from a simpler domain. Suppose we want to try to predict WHEN a mobile game users will make a purchase if given a sale. Almost every ...
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1answer
5k views

Demand Forecasting for Multiple Products Across Thousands of Stores

I'm currently working on a demand forecasting task, with data on tens of thousands of products across a couple thousand stores. More specifically,I have 3 years' worth of daily sales data per product ...
3
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1answer
337 views

How to get a feature from sound/audio data learning using machine learning supervised classification?

I'm a bit confused about how data in audio files can be processed for a ML classification model. I have several .wav files that contain dogs barking and cats "meowing". The pipeline is the following: ...
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1answer
3k views

Time series prediction of discontinuous data

In the context of time series prediction, I have read that time series is a series of data that taken at successive equally spaced points in time (which means its in order). What if I have a ...
3
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1answer
964 views

SARIMAX with seasonality greater than one year

I would use Statsmodels SARIMAX with data having seasonality greater than one year. In my case, I have seasonality equal 4 years, therefore I have tried: ...
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1answer
4k views

Anomaly Detection In Univariate Time Series Data Using ARIMA In Python With Updating

I have trained an ARIMA model on some 15 minute incremented time series data by using the statsmodels library. I would like to determine how anomalous the next 15 minute increment's data I observe is. ...
3
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1answer
226 views

Classification on time series data

Context: I am working on a classification project. where I recommend items to customers based on their past purchase history. Question: How will "time leakage" affect training? Example: Let's say ...
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1answer
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ARIMAX with spark-timeseries

Cloudera recently added the spark-time series library to github. According to the user docs, it definitely can fit autoregressive integrated moving average (ARIMA) models, but I see no mention of ...
3
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1answer
109 views

How to predict the duration of burst given several series

I've got sets of time series data collected from Weibo. It contains the number of posts under certain topics over a year. It can be found that from time to time there're bursts of discussion on ...
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Appropriate visualization for this kind of data

Late edit: currently working through the FlameGraphs bibliography here. It looks like what I'm doing is similar to an icicle chart, but with passage of time on the x-axis. The author mentions ...
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52 views

Detecting pushups based on pose data

I've been playing with Google's MLKit, and decided to detect push ups. As a quick test, I took the position of the left shoulder, and plotted the Y Axis. Here's how a variety of trials look: Five ...
3
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2answers
372 views

How to identify recurring patterns in this set of transactional data

I'm working on a dataset of banking transactions and would like to find recurrent transactions. I've been mapping transactions per merchant in timeseries, and tried to use acf from statsmodels.tsa....
3
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1answer
707 views

Python: forecast unevenly spaced time-series?

My data has timestamps corresponding to the failure occurrences of a specific component in machinery. The timestamps are not uniformly distributed. My question is: 1) what methods can I use to (almost)...
3
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1answer
41 views

preprocessing time sequence

I have a long list of event (400 unique events, sequence ~10M long). I want to train an RNN to predict next event. The preprocessing steps i took are: (1) turning to OneHotEncoding using pandas: <...
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How to apply a groupby rolling function to create multiple columns in the dataframe

I am setting up a volume profile series over a stock data. I have implemented the market profile code from this github repo and the link to the data is here and the example here. Some Sample of data ...
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2answers
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How can I approach this problem?

Let's say I have a dataset with pricing information for the same flight during the past year. So, for a flight departing on day D, I have the available price from D-130 up to D (departure day). Then ...
3
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1answer
85 views

How to update the posterior belief when we are observing a stream of correlated data from a fixed but unknown data source

I want to build a [probabilistic] model that aims to infer the true value of an unknown categorical variable, $y \in \{1,2,..., K\}$. We have a dataset $(X,y): \mathbb{R}^d\rightarrow \{1,2,..., K\}$ ...
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summarizing time series dataset: extract time window sliding, change points, pattern seasonality in time series

I need to detect list of change points in time series dataset (temperature), and I need to split dataset into set of classes (patterns) and detect seasonality of each class (pattern). for example ...
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2answers
158 views

Similarity Measure of Simulated Time Series vs Observed time Series

In my work I have an observed Time Series and Simulated ones. I want to compare the Light Curves and check for similarityto find out which simulated curve fits best respectivley which parameters ...
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47 views

Timeseries prediction error measurement. How to deal with diffrent time scales?

I have some time series and a prediction model. Now I would like to measure how good/bad the prediction is for different products. The problem is that for each product the time points (frequency of ...
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1answer
1k views

Advice on imputing temperature data with StatsModels MICE

This may be a dumb question but I can't figure out how to actually get the values imputed using StatsModels MICE back into my data. I have a dataframe (dfLocal) with hourly temperature records for ...

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