Questions tagged [time-series]

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

Filter by
Sorted by
Tagged with
0
votes
0answers
5 views

Multivariate time series forecast with VAR confusion

I am new to time-series forecasting. I am working now on a task in which I have a data set, containing samples of approx. 15 variables for every hour for several years. Then, I have a test data set (...
0
votes
0answers
10 views

How to train a NN with mutliple variables? [closed]

I have a csv file with following content (the full list has more entries): ...
0
votes
0answers
10 views

Time series forecasting in Python with 2 categorical variables

What approach is the best for a time series forecasting where you want to include 2 categorical variables in python? Im not finding any useful information that can help guide me with this; mainly ...
2
votes
1answer
19 views

Multi-output, multi-timestep sequence prediction with Keras

I've been searching for about three hours and I can't find an answer to a very simple question. I have a time series prediction problem. I am trying to use a Keras LSTM model (with a Dense at the end) ...
0
votes
0answers
9 views

Which statistical tool, for test of hypothesis, is appropriate to find p- value in a python time-series data? [closed]

I have a long-term timeseries dataset with hourly time resolution. I found daily average values for each day in a week. I could clearly see some weekly variation. But, I want to ascertain that the ...
1
vote
0answers
19 views

how to use CNN-LSTM with timedistributed

I am trying to use CNN-LSTM model with keras to reconstruct the time-series images, but now there are some weird problems. The input image is gray-scale and the input shape is ...
0
votes
0answers
9 views

Predict variable from time series when there are many observations in the same date

I have dataframe that is similar to this: ...
1
vote
2answers
28 views

Low scale ML/statistical techniques for data poor settings

I have two separate problems. One is logistic regression and other is time series prediction. But both suffer from paucity of data problems a) For logistic regression, I have tiny dataset with 10 ...
0
votes
0answers
11 views

Finding the wiggles pattern in the original dataset. (Wiggles appear after performing division by another dataset)

I have multiple measurements regarding scientific observations. The problem is that there is a subtle noise pattern caused by the instrument - the wiggles. These wiggles are invisible when looking at ...
0
votes
0answers
6 views

Forecasting mon missing time timeseries data

I have time series data for minutes interval. But due to some noise i have to remove some rows from data. Now, I have data with some missing time stamp. What should i do for forecasting in this case?
0
votes
0answers
3 views

Tier Splitting for Time Series Analysis K means

I am currently trying to expand upon some results from the paper "Time Warping Clustering for the Forecast and Analysis of COVID-19" by Qixuan Jin out of Cal Tech, because when it was ...
0
votes
0answers
11 views

In Time Series forecast, should Scaling be done on both train and test features combined ( test is 1 new data point)?

Let say I have a Time series, I'm using sliding/expanding window method to split to train and test data: train would be all the data I have until day x and test is day x+1. To avoid Data leakage I'm ...
0
votes
1answer
24 views

how can we feed both data time series and non time series data together in machine learning classification model

I have a dataset(IoT wearable dataset) composed of time-series and integer data; the objective of my task is to use the dataset for classification. Whilst current libraries in sktime accept ...
0
votes
1answer
29 views

How an input data flows through an lstm layer cells?

I make this sec2sec NN model for the purposes of learning: ...
1
vote
0answers
21 views

Machine Learning Model for Time Series Forecasting

I am using Random Forest, SVM, and XGBoost models to nowcast/forecast an economic time series variable. However, I would like to extend these models to optimize/customize them for time series ...
0
votes
1answer
37 views

Facebook Prophet add Regressor

I've been searching for a long time to answer my question, but I haven't found anything. So I hope you can help. I'm searching for an opportunity to add a regressor to my prophet model in python. I ...
1
vote
0answers
22 views

One Year Ahead Forecasting with Unevenly Spaced Time Series

I have many products in my warehouses which can be "demanded" any day by my different clients. I want to forecast how many of each item will be demanded for the whole next year. Naturally, ...
0
votes
0answers
6 views

time series prediction training on multiple lags using tensorflow 2

I am just studying tensorflow 2. Here is where I learned time series training on multiple lags using LSTM: https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/ In this ...
0
votes
0answers
14 views

How to fill missing latitude and longitude values in time series data?

I have time-series data like this: date longitude latitude 01/01/2010 -5.42766 107.5784 02/01/2010 -6.42728 104.5245 07/01/2010 -7.42702 105.5816 14/01/2010 -4.42728 99.57834 17/01/2010 -6.41523 ...
1
vote
2answers
31 views

How to convert longitude and latitude in time series data from daily to weekly?

I have time series data like this: date longitude latitude 01/01/2010 -5.42766 107.5784 02/01/2010 -6.42728 104.5245 07/01/2010 -7.42702 105.5816 14/01/2010 -4.42728 99.57834 17/01/2010 -6.41523 ...
2
votes
0answers
21 views

CNN regression. help to improve current model [closed]

I have time series grey scale images that show movement of fluid with different densities. I want to predict a pixel value for time t, with (t-3),(t-2),(t-1) 2D images as inputs. I am figuring out how ...
0
votes
0answers
5 views

Multiple step prediction for non-time series

I have a public EHR dataset which contains info on a) lab tests b) diagnosis c) surgical procedures d) drugs prescribed etc Now, using the above data elements, I would like to predict the below a) ...
0
votes
1answer
29 views

M1 MacBooks versus Google Colab

I am just starting getting into deep learning with tf.keras. I am at the point where I have to decide where I want to develop. The thesis project will be timeseries ...
0
votes
0answers
10 views

Time series forecasting with RNN(stateful LSTM) produces constant values? Is there any solution out there?

I tried lstm but results were getting constant. Same question as in the link
0
votes
0answers
15 views

ValueError: Found input variables with inconsistent numbers of samples: [367, 24]

Working on a Time Series model that was 730 days with of revenue data and I have two questions. First, I'm a little confused on how many days I should set my train and test split to. Currently, it's ...
0
votes
1answer
13 views

X Second samples taken on unevenly spaced intervals

I have dataset of following specification: 512 samples taken at unevenly spaced intervals over the year Each sample is an 8 second data from sensors with 4ms resolution Samples are not labeled For ...
0
votes
0answers
12 views

Data augmentation for tabular data in a multi label classification task

The task at hand is to predict the future lab values for a patient (1 if abnormal and 0 if normal) using the previous numerical data. It is a multi-label, multi-class time series classification task. ...
0
votes
0answers
11 views

Anomaly Detection in Highly Variable Time-Series Data

I am trying to detect anomalies through a column called count. The data is a time-series data and it is present for every 5 minutes for each day. The dataframe looks like this: ...
0
votes
0answers
5 views

Time series forecasting for stable pattern with some sudden changes

In my case, the time series is around a constant value with very small fluctuations. But, sometimes the signal starts increasing or decreasing for some duration of time. For my application, such ...
0
votes
1answer
29 views

How can I split hourly time series?

I'm newbie in R and time series analysis. I'm trying to build an Arima model. My dataset has this structure: ...
0
votes
0answers
12 views

Analysing Time Series Model performance

Tried to forecast the target variable using Holt's Winter Additive model. Its a univariate dataset with 6409 data points. I took a subset of 100 points. Getting best RMSE is 48220. Min value of target ...
0
votes
0answers
9 views

Is it Worth Installing Cesium on Windows?

I am using Python(Anaconda package). I know Cesium requires a Cython and a C/C++ complier because I have a windows computer. I was looking at the installation instructions and it appears to be ...
0
votes
0answers
8 views

Time series forecasting when one of the series is known

I have a problem where there are two time series $\{x_t\}_{t \geq 1}$ and $\{z_t\}_{t \geq 1}$. These two time series are correlated for fixed time instant but uncorrelated with each other across time....
1
vote
0answers
39 views

Which One is the Best Way to Create Training Sequences for LSTM-based Class Prediction on Time-series Data?

Let's say I have time-series data in the following way. I need to create training sequences of a fixed length as an input to my LSTM model on PyTorch. ...
0
votes
1answer
14 views

How to determine precision level of outcome in ML models?

I understand there are lot of ML products that can help predict the time to event. For ex, customer will purchase in the next 30 days or Patient has chances of re-...
0
votes
0answers
9 views

Where is publically available time-series RCT data?

Our team is writing a paper about uplift modeling considering time heterogeneity using Machine Learning model and Causal Inference theory; the example would be like, in marketing, a model maximizing ...
0
votes
0answers
25 views

Predicting out-of-sample time points with LSTM

I'm working on a time series forecasting problem using LSTM. The data is univariate and non-stationary. I followed the this tutorial. The data is processed as the following: First, the difference ...
1
vote
1answer
35 views

Is time series forecasting possible with a transformer?

For my bachelor project I've been tasked with making a transformer that can forecast time series data, specifically powergrid data. I need to take a univariate time series of length N, that can then ...
-1
votes
1answer
38 views

Neural network for time series forecasting with an auxiliary data

Lets say we have 2 data sets. First is the close price time series data set and we want to predict future values of it. The second is volumes of each price from the first data set and we do not want ...
1
vote
0answers
9 views
0
votes
0answers
29 views

Synchronizing timestamps between multiple sources of time-series data that are both asynchronous and imprecise

I have time-series data coming from multiple sources. The data from each source arrives at a "roughly known" interval (i.e. once per hour), but the timestamps across the sources are not ...
0
votes
0answers
24 views

How to Classify Game Stages Based on Bitrate Time Series Data

I need suggestions for my project and would be glad if you would give me a hand. I have a dataset of frames obtained from the old-school game DOOM. Each frame in the dataset has the following columns: ...
0
votes
0answers
24 views

Neural net performance using rmse

I am trying to build a NN which can predict exchange values. I am quite new to R and NN and I don't quite understand how I could improve the performance metrics of the neural network. I have tried ...
0
votes
1answer
23 views

I'm trying to do a time series model without a datetime field in python. Is this possible?

I have a dataset with data like this: Day Revenue 1 1.2 2 1.5 3 1.1 4 1.34 I want to do a time series model on it, but am ...
1
vote
1answer
28 views

How can I plot a line for time series data with categorical intervals in R

I am working with single time-series measurements that I want to plot for the time window of about 1 week. This is the data I am working with. This is my R script: ...
0
votes
1answer
21 views

How to get periodicity from timeseries data?

I would like to create a recommendation system for a smart home application. I gather the data in a time-series database. The app monitors the on/off state of a smart lamp and can create daily ...
0
votes
0answers
15 views

LSTM with multiple entries for the same timestamp

I have a dataset where I have multiple entries for the same timestamp and I want to use LSTM to forecast the next timestamp given the previous 5 timesteps. From https://machinelearningmastery.com/...
1
vote
0answers
16 views

Predicting sparse time series data

I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0's, since there is no continuous flow of cars coming to charge but rather ...
1
vote
0answers
7 views

Modeling Scaled Residuals

I found a good model for a time series forecasting problem I have but it doesn't allow for covariates, which I need to include a few of (date-based events). The approach I came up with to deal with ...
0
votes
0answers
10 views

Do Any Frameworks Provide Better Support for End-To-End Integer-Based Feature Engineering, Modeling, and Inference?

A retail enterprise I work with with wants to switch from its home-grown time series data analysis and prediction system to something more established and with community support. One unique feature ...

1
2 3 4 5
28