Questions tagged [time-series]
Time series are data observed over time (either in continuous time or at discrete time periods).
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questions
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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 (...
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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):
...
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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 ...
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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) ...
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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 ...
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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 ...
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9 views
Predict variable from time series when there are many observations in the same date
I have dataframe that is similar to this:
...
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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 ...
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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 ...
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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?
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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 ...
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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 ...
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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 ...
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1answer
29 views
How an input data flows through an lstm layer cells?
I make this sec2sec NN model for the purposes of learning:
...
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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 ...
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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 ...
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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, ...
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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 ...
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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
...
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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 ...
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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) ...
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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 ...
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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
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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
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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 ...
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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. ...
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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:
...
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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
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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:
...
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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 ...
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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 ...
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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....
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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
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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-...
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0answers
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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:
...
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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
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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
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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 ...
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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/...
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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 ...
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0answers
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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 ...
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0answers
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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 ...
