Questions tagged [time-series]

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

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Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$...
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2answers
2k views

Forecasting Multiple (few hundreds) uni-variate time series with inflated zeros

Hello Practitioners, Being a newbie seeking help to gain experience in Data Science. Lets take a scenario where a big company wants to forecast its sales (a specific product) across different stores ...
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2answers
71 views

Detecting abundance of a certain periodic pattern in a time series?

I am really stumped at the moment about how to solve a particular problem. I have many time series like this: This represents the number of hours a person spends on a website each day throughout the ...
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1answer
662 views

Time Series pattern recognition and classification problem

I have some labeled sensor data. Now, I would like to know how to extract features from time series using DFT, DWT, and HAAR transforms. I know that the transformations above transform a signal to ...
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3answers
242 views

Cluster evolution over time

I have a dataset of transactional data with customer ID and I want to segment the dataset into groups using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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0answers
41 views

Applying Differencing on a time series, before or after train and test split?

I am attempting to improve my RNN model by making my dependent variable, a stock price, non-stationary. I am aiming to make the series stationary by removing the trend with a log transformation and ...
4
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0answers
89 views

Repeated k-fold Cross Validation for time series data?

I have a relative small sample size (330 with 45 features) + it's time series data. I want to train my LightGBM regression model for best generalized RMSE score and want to use repeated CV. I use ...
4
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1answer
3k views

Autoencoders for the compression of time series

I am trying to use autoencoder (simple, convolutional, LSTM) to compress time series. Here are the models I tried. Simple autoencoder: ...
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0answers
55 views

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 ...
4
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1answer
823 views

Train LSTM model with multiple time series

I am predicting energy usage for a bedroom within a school residential building with date, temperature, and humidity as input features, using 7 time-steps and ...
4
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1answer
4k views

Monthly trend with fb prophet-Interpreting the graph

I have monthly data with month/year in one column and price on another. I would like to get a yearly trend with fb prophet library in python (how to use monthly data with the library is explained at ...
4
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1answer
496 views

k-Nearest Neighbours with time series data - how to obtain whole-time-period estimators

I have a large dataset for the activities performed by multiple staff in a factory over a long period of time - 01/01/2017 - present. The activities performed by the different staff are recorded at ...
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75 views

Classify driver based on time-series sensor data

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
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 ...
4
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1answer
11k views

Plot of ACF & PACF

There are 96 observations of energy consumption per day from 01/05/2016 - 31/05/2017. I am trying an ARIMA model in R to be fitted to these time series observations. I have chosen the frequency of ...
4
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3answers
259 views

How can one generate future forecasts from probabilistic events?

I have an event "whether an item sold will be returned or not" which I can predict with a certain probability based on information gathered at the time that the purchase occurs (product features, ...
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51 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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73 views

How to find lagged cross correlation between time series?

I have 2 time series, $X$ and $Y$, and I'm trying to find the best lag range that correlates $X$ to $Y$ (find the amount(s) of lag of $X$ that best correlate to the target variable $Y$). For instance, ...
3
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2answers
328 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
39 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: <...
3
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0answers
2k views

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 ...
3
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2answers
74 views

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
84 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
150 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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0answers
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 ...
3
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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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0answers
35 views

Keras 'cross section' model with time trend

Problem: I have a problem in which cross-sectional features (X) explain a continuous outcome (y). In addition, there is a linear time trend (t) in the data. Using OLS, such a model would write: $y = ...
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0answers
162 views

Time series pattern recognition

I have measured stress at 1 million points inside a material at 100 time steps. I have made a probability distribution plot for three time steps and I see that the evolution of stress looks like this: ...
3
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1answer
154 views

Clustering time series based on monotonic similarity

Context I am involved in the task of clustering 1500 time series of 500 observations into a few clusters. The time series share all the same observed properties at different spatial locations, but ...
3
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2answers
562 views

Dealing with time series data which has multiple observations for the same timestamp

I have a time series data in Python 3 as follows: ...
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0answers
286 views

Multivariate time Series classification - One class

I need your help with time series classification. I have measurements of different medical parameters for patients captured at every one hour. The output label is whether the patient has Acute Kidney ...
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0answers
209 views

Layman's explanation of when to use which smoother algorithm/technique: FFT, loess, Savitzky-Golay, etc

As an analytics practitioner, I frequently come across noisy data (e.g. IoT data). When building a model or machine learning algorithm, it can be advantageous to smooth this data. Over the years, I ...
3
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1answer
43 views

Detect Missing Records in Dataset

I have a dataset that contains several measures from various widgets on a daily basis. While the widgets remain relatively stable over time, sometimes there are legitimate reasons for one to disappear ...
3
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1answer
91 views

Need help on Time Series ARIMA Model

I'm working on forecasting daily volumes and have used time series model to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
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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)...
3
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1answer
214 views

Data normalization in nonstationary data classification with Learn++.NSE based on MLP

I need to predict technical aggregate condition using vibration monitoring data. We consider this data to be nonstationary i.e. distribution parameters and descriptive statistics are not constant. I ...
3
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3answers
88 views

Find recurrent dates in a small set (and get rid of non recurrent ones)

I need help in the analyse of a categorization problem. Given a set of dates (small set: 20 elements maximum), I would like to group dates which are equally distributed (with a tolerance). It can be,...
3
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0answers
951 views

Predict event likelihood given time of other events

On a daily basis there is a sequence of events. Each event may or may not occur on a given day. Given the times of the preceding events for the current day I want to be able to say whether there is ...
3
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2answers
273 views

how to calculate p value

I need to calculate statistical significance between two time series, each with 4500 terms. My null hypothesis is that $H_0: \mu=\mu_0$ (value in time t of first time series is equal to value in time ...
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0answers
102 views

How to find a model for a short discrete time-series?

I'm examining the activity of customers over the years which have about one event per year. This results is many short time-series for which I found the distributions (hit/miss over 4 years sorted by ...
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0answers
23 views

Cross correlation

I am trying to find a good algo (low latency) that is able to take two time series and determine which one is leading on the other one if any. The time series do not necessarily have the same ...
2
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1answer
28 views

ML model to forecast time series data

This question has three sub-parts, answering each of which probably doesn't require huge text. I hope that is okay. I'm trying to understand time series prediction using ML. I have the target variable ...
2
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0answers
26 views

Static ML model or Time-Series? How to model/predict a binary target when I have time variant features but most features are constant?

I have been working with Real World data from patients. I have a dataset with information about 10million patients; Collected over a span of varying duration (5 to 20 years). What I am predicting is ...
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0answers
17 views

How to modify a Convolutional Neural Network architecture built for a univariate time series to multivariate time series?

I have built a CNN (in combination with a LSTM cell) that takes 1D time series-like data as an input and performs classification. I am obtaining a good performance, but the complete data has actually ...
2
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1answer
63 views

How to treat patients without events in time-to-event analysis?

I'm working with longitudinal data for a series of patients. Duration of followup on a patient-level is non-uniform. Patients can either experience a discrete event (e.g., a heart attack) or never ...
2
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0answers
16 views

Predicting millions of sparse timeseries using them to help each other

This is a very general problem faced by different types of businesses. Predict the future behavior of customers over time. Imagine that we have 1 million customers with their own features over time, ...
2
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1answer
37 views

Best Way to tackle to time series classification problem?

I have a dataset where the input is a dataset for ICU patients where each ICU stay has 40 features (20 vitals, 20 lab values) and multiple time steps (the stays' length is between 6 and 19-time steps)....
2
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1answer
15 views

Architectures that take inputs of mixed sampling rates

Let's say a model is trained on multiple datasets of 1D time series. These datasets have been gathered with different sampling rates. I plan to use a convolution neural network to process these time ...
2
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1answer
20 views

Suggestions for improvement? Time series of variation in relative frequency of emotion-related words in academic psychology over time

First time plotting and interpreting time series data and I have used a line plot for ease of use. I am aware this is incredibly basic, but any input/ recommendations would be much appreciated (e.g., ...

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