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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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Triangle Pattern Recognition on Financial Market with Python

I'm working on a personal project to find Triangles on any stock in Python. I detect the max and min points (shift(-5,+5) because if I consider only shift(-1+1) I have a lot of lines) and write lines ...
Martin Bouhier's user avatar
6 votes
0 answers
92 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 ...
Jor_El's user avatar
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6 votes
0 answers
99 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 ...
John Karimov's user avatar
5 votes
1 answer
652 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 ...
Statsanalyst's user avatar
4 votes
2 answers
4k 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: ...
netang's user avatar
  • 41
4 votes
1 answer
311 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 ...
Delforge's user avatar
  • 193
3 votes
0 answers
41 views

Can we recognize different events in time-series data by patterns?

I'm currently have to deal with multiple time-series datasets with the same type of patterns. My quest is to find a way to label these data points (or may be intervals) correctly. Below is how the ...
duy quan duc's user avatar
3 votes
2 answers
61 views

How to detect whether an entire series is an outlier relative to others?

I have multiple price series of the same asset as follows. Visually, it is obvious that series "A" (the flat line) is an outlier, and series "E" (the line with the zig-zag pattern)...
finstats's user avatar
  • 131
3 votes
1 answer
146 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 ...
user9343456's user avatar
3 votes
0 answers
118 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 ...
Stepan Parunashvili's user avatar
3 votes
0 answers
455 views

Data leakage in bidirectional LSTM timeseries data

Does it cause data leakage to train a bidirectional LSTM on data where a user can be a sample in the training data multiple times? Each row is a snapshot at a different point in time for a given ...
David Feldman's user avatar
3 votes
1 answer
84 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: <...
Guy Barash's user avatar
3 votes
1 answer
278 views

time series prediction using arima and non linear trend and too much residuals

I am working on forecasting a financial index, i tried decomposing the time series using : ...
BalticOY's user avatar
3 votes
0 answers
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 ...
Scrappy Coco's user avatar
3 votes
1 answer
54 views

Approach to classify blocks of time series

I am wondering if there exists an approach to classify blocks of time series, and not specifically individual time series. If so, can you point me out papers/articles/tutorials where these type of ...
YellowishLight's user avatar
3 votes
2 answers
109 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 ...
raulb1's user avatar
  • 87
3 votes
1 answer
103 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 $(X,y): \mathbb{R}^d\rightarrow \{1,2,..., K\}$ ...
Mo-'s user avatar
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3 votes
0 answers
92 views

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 ...
Mina Younan's user avatar
3 votes
2 answers
347 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 ...
Wiesel's user avatar
  • 51
3 votes
1 answer
98 views

What Models should i try for this problem?

I need some advice for a problem i'm working on with automobile data. The vehicles provide a series of codes at every second which are bieng stored, though it can vary how many. For example , at time ...
Parth Sindhu's user avatar
3 votes
0 answers
59 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 ...
MichaelRazum's user avatar
3 votes
2 answers
932 views

ARIMA forecast for timeseries is one step ahead

I'm trying to forecast timeseries with ARIMA. As you can see from the plot, the forecast is one step ahead of the expected values. I read in some other threads that this behavior is expected but how? ...
mobelahcen's user avatar
3 votes
0 answers
60 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 = ...
Peter's user avatar
  • 7,526
3 votes
0 answers
251 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: ...
user134439's user avatar
3 votes
1 answer
1k views

Whole time column in csv file convert into UTC (epoch) using python

I have a dataset with time and columns. I want to plot a graph with time and value. I tried many methods but didn't come proper graph. Because I have a time series. Then I thought I will convert time ...
user avatar
3 votes
2 answers
2k 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: ...
deathcode 666's user avatar
3 votes
0 answers
362 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 ...
The Great's user avatar
  • 2,575
3 votes
1 answer
4k views

Predicting next number in a sequence - data analysis

I am a machine learning newbie and I am working on a project where I'm given a sequence of integers all of which are in the range 0 to 70. My goal is to predict the next integer in the sequence given ...
varun's user avatar
  • 31
3 votes
0 answers
400 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 ...
JasonAizkalns's user avatar
3 votes
1 answer
80 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 ...
Skiddles's user avatar
  • 988
3 votes
1 answer
306 views

Feature selection for time series prediction

I'm working on an LSTM-based stock market forecasting problem and trying to figure out a way to select input variables. When calculating correlation between variables (e.g. Close price of Tesla vs ...
Leandro Ercoli's user avatar
3 votes
0 answers
377 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)...
Eulenfuchswiesel's user avatar
3 votes
1 answer
304 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 ...
Alexander Okunev's user avatar
3 votes
0 answers
222 views

Methods for analyzing multiple time series

My agenda is finding patterns and possible a model that describe my data. My data is comprised of multiple time-series uni-variate sets. ...
yoav_aaa's user avatar
  • 993
3 votes
3 answers
109 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,...
Damien's user avatar
  • 31
3 votes
0 answers
1k 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 ...
CoderBrien's user avatar
3 votes
0 answers
117 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 ...
Gere's user avatar
  • 355
2 votes
1 answer
47 views

How to analyze time series data and create time series model in Python?

I am trying to understand time-series data and model. In youtube tutorial and others, mostly univariate examples are shown. And they are applicable or suitable for those conditions. What if our ...
Bad Coder's user avatar
2 votes
0 answers
22 views

How to properly select features for time series ML models

I've been trying to get good references on how to solve a problem that's been bothering me regarding the modelling techniques I've used. I'm currently interested in making forecasts using ML for ...
loguimaraes's user avatar
2 votes
0 answers
118 views

LSTM output capped at a maximum

I am using a LSTM built using to forecast a single-value (solar irradiance) by using weather data as my input. When predicting my validation test, I get a weird results as it looks like all my ...
Adam Jaamour's user avatar
2 votes
0 answers
72 views

Why my LSTM model always start a prediction with the same pattern?

I want to find out why my LSTM NN always starts the forecast with a peak. This is my model: And those are some Predictions: If you check that the red line always starts with a peak, can someone ...
Nathaldien's user avatar
2 votes
0 answers
218 views

Detecting Data Drift in Audio Data

For a give set of audio files collected from an industrial process via a microphone, I have extracted suitable features and fed them into a neural network for training a binary classifier as depicted ...
TwinPenguins's user avatar
  • 4,279
2 votes
0 answers
26 views

Is my dataset a time series dataset? and should I use an LSTM

I have a dataset where I am recording temperature after every 4milliseconds till 500 and another feature 'conductivity value'. The length of the dataset is around a 1000 rows. I need to find the ...
Araib karim's user avatar
2 votes
0 answers
30 views

Why does a linear regression in time series forecasting does not provide a line in predictions?

I'm reading the TensorFlow Time Series forecasting Tutorial 1 trying to perform my own time series prediction. However, specifically on single-shot models section for multiple time steps, the Linear ...
Samuel Gomes's user avatar
2 votes
0 answers
32 views

Models for Long-Term Time-Series Forecasting and Pattern Recognition

I'm trying to find a solution for long-term electricity hourly prices forecasting. Explaining simply, I have some data from 2018 - 2021 containing Demand, Renewable Generation, Hydropower Generation, ...
Ircb's user avatar
  • 21
2 votes
0 answers
264 views

Why the LSTM on Keras does not work correctly when it is necessary to predict several steps forward

I used AirPassenger Dataset. And based on several previous values(for examples 20) I want to predict several(3 or 5) steps in future. Like X -> y [10,20,30,....200]->[210,220,230] [20,30,40,.......
Vladimir Shebuniayeu's user avatar
2 votes
0 answers
1k views

Grouped Time Series forecasting with scikit-hts

I am trying to forecast sales for multiple time series I took from kaggle's Store item demand forecasting challenge. It consists of a long format time series for 10 stores and 50 items resulting in ...
Downforu's user avatar
  • 131
2 votes
0 answers
779 views

Multiple Entities, Multivariate, Multi-step - Time Series Prediction - Python

My goal is to create a time series model with Multiple Entities - I have multiple products with pre orders and they all have the a similar bell shaped curve peeking at the release date of the product ...
sogu's user avatar
  • 145
2 votes
0 answers
43 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 ...
percojazz's user avatar
  • 121
2 votes
2 answers
101 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 ...
cavosch's user avatar
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