modeltime: Time series forecasting in R with tidymodels

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An introduction to our forecasting package, #modeltime. Modeltime extends the tidymodels ecosystem for time series forecasting. Learn how to forecast with #ARIMA, #prophet, and linear regression #timeseries models.

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TABLE OF CONTENTS
00:00 Introduction to Modeltime
00:30 GitHub Project Setup
01:03 Libraries: Modeltime & Tidymodels
01:48 Data: DC Bike Sharing Daily
02:59 Train/Test Split
03:39 Forecasting (is Exciting!)
03:49 ARIMA (Automatic)
04:40 Prophet
05:24 GLMNET (Machine Learning)
06:32 Modeltime Workflow
06:46 Modeltime Table & Modeltime Calibrate
07:32 Modeltime Accuracy
08:12 Modeltime Forecast (Visualize Test Set)
09:00 Modeltime Refit & Forecast (Visualize Future Forecast)
09:42 How to Learn More!

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Great package for forecasting. Thanks, Matt!

jgeise

Awesome package. That interactive plot is also really cool! I’m not too familiar with time series…how would you handle forecasting customers for the year ahead when working with five years of data and COVID as a separate phenomenon over the last two years only?

PA_hunter

Great tutorial I am gonna register for the course! One question I usually deal with data that is reported yearly how can I define the model to use yearly step data and not monthly?

jossrdgz

Hi...great work! can i do it with irregular time series?

wilsoncarrillo

Since modeltime extend tidymodels, can i use explainable methods used in tidymodels like vip, DALEX and DALEXtra? It would be amazing explain the forecast with modelStudio

Great tutorial. Please, how can I add regressor? I need to include a xreg to help improve the prediction.

rafaelbaptista

Great video, thanks for the easy to follow explanations. I have been getting an error once I get to the ARIMA model: Error in `check_case_weights()`:
! 'case_weights' should be a single numeric vector of class 'hardhat_case_weights'. Do you know what it means?

cgonzalezcon

Hi, Why aren't forecast intervals getting wider as we move further into the future? Thanks

anitahaique

Hello excellent video!. At minute 8:50, how do I put the same colors on the legend labels? Thank you

maxirojo

when I try to run'modeltime' Error shoed as: package or namespace load failed for ‘modeltime’:
.onLoad failed in loadNamespace() for 'modeltime', details:
call: error: Model `prophet_reg` already exists. Could U pls tell me how to resolve it?

jerrickren

Doing the proper code, what we do grid search for the parameters?

sebastiansantiago

Hi, does this support Neural Net based time series and Bayesian Structural Time Series?

emiliostar

Using date_var: Date
Error in `dplyr::group_by()`:
! Column `Date` (index) can't be a grouping variable for a tsibble.
i Did you mean `index_by()`?

i got this error when i terminate R session please help

PAULSHOWTO

Hi! Please could you review the time_series_split function? There is something wrong on how the function is making the split (asses property not really taking dates into account and maybe using sample count?). If your dataset samples don't have daily registers the test date range will not be as stated. Have mapped dividing by items and got diferent test date ranges for each item.
Anyway, thank you a lot for your work and teachings!

patuko

How well do these packages work with annual data rather than daily/monthly/quarterly?

ericmai

greetings, Is there a way to see the raw data for the predictions. The variables show model information, not the raw projected data ..

NotMuchHere

On the plot_modeltime_forecast output, it is a bit difficult to see the colors on the legend. Is there parameter to change in make the color larger or standout more on the legend?

Ottozone

I am using the nbeats model for time series forecasting. Everything looks fine except am getting some rlang error : can’t find nbeats environment. When clear the state and reattach the cluster in databricks, the error goes. Can someone suggest how the error can be fixed

aparnasnayanar

Never really understood the use of time series forecasting that merely replicates seasonal patterns. I could have come up with those forecasts by my self just by looking at the series previous months. So many advanced algorithms yet they do not perform better than a human.

Arkantosi

how to check the MAPE and RMSE of forecast?

PAULSHOWTO

modeltime: Time series forecasting in R with tidymodels

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