Questions tagged [time-series]

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

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1answer
44 views

LSTM for time series forcasting

I manipulate the time series using the different structures of the neural networks in order to make a prediction, and I wonder if there is a way to choose the parameters of the networks intelligently? ...
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5answers
29k views

Additive vs Multiplicative model in Time Series Data

The above time series plot is a daily closing stock index of a company. I want to know which model between additive and multiplicative best suits the above data. I know what the two models are, but i ...
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1answer
65 views

time series anomaly detection

I want to ask for time series anomaly detection we can apply tnn on multiple features or not? I used transformer for sentiment analysis where I have to provide a sentence and it predicts its output as ...
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1answer
346 views

Python: SARIMAX Model Fits too slow

I have a time series data with the date and temperature records of a city. Following are my observations from the time series ...
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1answer
53 views

Using sensor data and a know reference point infer the position of a moving robot

Say, the robot is starting at a known position and I've data coming off of the robot as it traverses the grid layout. Exploiting the nuances captured in the data - like the implication of unequal rpm ...
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1answer
13 views

What are some deep learning models use in timeseries forecasting that include context from covariates?

I was going through the literature for time-series forecasting using DL and all the methods I read about only use the variable of interest at previous timesteps to predict the same variable at time ...
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0answers
32 views

Imaging multivariate time series for 2D CNN classification

I have multivariate time series data in the shape of (batches, timesteps, features). So, for 10 samples with 20 timesteps and 4 features, my dataset shape is (10,20,4). I have been using this data for ...
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0answers
6 views

Is it possible to create a single time series forecasting model to encompass several subseries?

Let's say that I have a univariate time series that measures aggregate sales across all of my company's customers, with daily frequency for a whole year. Using this time series as my dataset, I ...
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1answer
66 views

predicition for a specific month

I am attempting to build a predictive model based on the past historical data. I have details of specific machine failure based on the past year data. I have data from some months of 2016 and from ...
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1answer
53 views

How to manage missing data in meteorological time series?

How to know the type of missing data is what it is: MCAR, MAR or NMAR, knowing that I'm working on time series multivariate, and is that going to help me deal with the missing data, and what is the ...
2
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1answer
680 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 ...
2
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1answer
170 views

Clustering events in a sequence.

I've a sequence of recurring events I want to group together into representing different operation activities of the underlying process. 1) These events might potentially have an order in their ...
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1answer
20 views

Time series forecasting with constraints

I want to predict the passenger flow volume of an airline route, which subjects to supply capacity constraints of the route (i.e., the passenger flow volume should not be higher than the supply ...
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0answers
61 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 ...
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1answer
157 views

Fully endogenous models for predicting multivariate time series

I have a formal social science background but I am new to data science. My interest is in building predictive models for applications in the social sciences, mostly (but not only) in economics. I am ...
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1answer
128 views

Alternative methods for novelty detection and correlations

Hey mates I have the following project: Imagine having two datasets A and B. Each dataset consits of 101 time series with the ...
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0answers
21 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,.......
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2answers
63 views

LSTM model, poor performance

I have been working on a project on the demand for a product. I am using data from 2016 to train the LSTM model. The architecture is as follows: ...
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1answer
204 views
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1answer
80 views

How to change parameters in LSTM for multivariate binary classification time series?

https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/ I am trying to follow this tutorial's code with a slightly different dataset, where the predictor is a 0 or 1: ...
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0answers
8 views

Conceptual question - is it correct to use categorical variables such as day, month, year as a fixed sequence input in LSTM?

I am working on a problem where I have to try to predict the dependent variable (continuous) every hour based on hourly temperature (the single continuous variable in predictor space), along with 4 ...
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1answer
30 views

When to tune hyperparameters in deep learning

I am currently playing around with different CNN and LSTM model architectures for my multivariate time series classification problem. I can achieve validation accuracy of better than 50 %. I would ...
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1answer
99 views

Time series on syslogs

Is time series model suitable for network syslogs considering the fact the messages are sequential and the messages are outputted as a result of dependency between themselves which can range from ...
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0answers
10 views

How to find the lag that shows highest correlation between two time series variables?

I have two variables in my time series data (X1,X2). I need to find the correlation between these two variables at different lags and identify the lag that shows the highest correlation. For e.g. I ...
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1answer
11 views

Regression prediction for HVAC unit Best way to utilize available data?

I am starting to investigate machine learning applications for HVAC at the commercial level. I am an HVAC controls person by trade that has recently taken some basic courses on Machine learning and ...
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1answer
28 views

which statistical parameters are more useful to detect anomalies and outlier? mean max min var?

This time series contains some time frame which each of them are 8K (frequencies)*151 (time samples) in 0.5 sec [overall 1.2288 millions samples per half a second) I need to find anomalous based on ...
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1answer
52 views

A multivariate linear regression for explaining impacts of the predictors

I am trying to build a multivariate linear regression and the main goal is to understand how the various features impact the response by understanding the coefficients and their confidence intervals. ...
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0answers
13 views

Find part of the signal that causes most of the noise

We are given around 20 time series. Each one of them is how many products were sold every day (and they have different volume, different mean and std). The main goal is to predict the total sum of ...
2
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1answer
101 views

Time Series Generation - Multi Dimensional Time Series Data

Disclaimer: Mathematicians please don't be mad at me for the use of some of the terminologies in this post. I am an Engineer. :-) Background: So I am currently working on a problem where I have to ...
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0answers
20 views

How to use time series forecasts as input features?

I have a time series dataset containing daily data like below. Let's assume that I would like to make some forecasts of my temporal serie (x) and use it as a second feature feature (f) to predict the ...
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0answers
19 views

How to avoid Naïve Time Series Forecasting

I'm trying different deep learning models for time series prediction (Bitcoin Price), But the results are too good to Be true and I'm suspecting that the model is just learning to copy previous values ...
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1answer
73 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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1answer
32 views

Unsynchronized time series visualization

I would like to visualize a large amount of events composed of time serie windows. A typical event would be: Problem is, my events are not synchronized, and so if I plot them all, it would look like: ...
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1answer
229 views

Machine Learning based Multivariate Time Series Prediction - How to create supervised data format

Q1: I have a multivariate time series dataset. For each timestep, there are 11 features and 1 output. I am going to use supervised ML to predect the output. I understand that in univariate cases, if ...
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0answers
12 views

LSTM or GRU for Time-series Multilabel classification

Univariate time series data with only one feature vector (e.g. 1x1300 as a time step), a superposition or sum of different signals, should be disaggregated or ...
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1answer
71 views

Univariate Outlier Detection

Let's say I have a dataset with the following format: customerid product orders_in_last7days orders_in_last6days orders_in_last5days orders_in_last4days orders_in_last3days orders_in_last2days ...
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1answer
55 views

Regression with LSTM network: use multiple time series as input

I've spent a few days on this and am starting to think I'm missing the obvious solution as this doesn't seem like a very uncommon problem. As an example dataset: I have 100 measurements with each a ...
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2answers
12k 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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2answers
472 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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3answers
2k views

Multi-Source Time Series Data Prediction

I was wondering if anyone has experience with time series prediction for data from multiple sources. So for instance, time series $a,b,..,z$ each have their own shape, some may be correlated with ...
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0answers
46 views

LSTM Shapley Deep Explainer TimeseriesGenerator Keras

I have this data in the form: X_train shape: (2724, 10) , y_train shape: (2724,) X_test shape: (682, 10) , y_test shape: (682,) which I feed into Keras' ...
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1answer
32 views

MY lstm has a really low accuracy, is there anyway to improve it?

I am trying to make a model to classify whether these patients can be diagnosed with dementia by their 35 days of biometric data. A brief summary of a dataset is below. as an input X_train data, it ...
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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0answers
21 views

LSTM and CNN - feature engineering and order for time series classification

My questions are related to multivariate time series classification, hence it may differ from forecasting problems. I can have either variable (entire history of the series) or fixed time steps (...
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3answers
1k views

Training and test split for time series analysis

I need help with below code: ...
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2answers
2k views

Data Conversion to Time Series in R

I have sales data for 2018 and 2019. I would like to convert it to time series. The data does not have daily sales: ...
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0answers
15 views

Detecting a Piecewise, Noisy, Linear Signal, with Constant Slope and Changing Y-Intercepts

I am trying to algorithmically detect a 2D linear signal under some noisy data. It is almost a textbook candidate for Robust Linear Regression, except for the fact that, while the slope remains ...
3
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1answer
45 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 ...
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2answers
332 views

Train MLP Neural Network on time series data?

Newbie question here but I was curious to ask if an MLP Neural type network can be trained on time series data? The dataset that I have is an electricity type data set from a building power meter and ...
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1answer
42 views

Conditional variational autoencoder: Feeding labeled MNIST to encoder with Keras

I am looking for a code implementation of a CVAE using MNIST in Keras. I found this Youtube video: https://youtu.be/8wrLjnQ7EWQ that does VAE, but I am not sure how do I convert this and make encoder ...

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