Based on a trained SARIMAX model given at the model input port of this node, the forecast values are computed. This apply node can also be used to update exogenous variable data for forecasting.
SARIMAX Predictor settings to configure the forecasts generated by the input model.
Table containing exogenous column for making forecasts on the SARIMAX model, must contain a numeric column with no missing values and of length equal to the number of forecasts to be made.
Check this box if you applied the log transform inside the SARIMAX Forecaster node while training your model. It will reverse the transform before generating forecasts
Forecasts of the given time series h period ahead of the training data.
Check this box to use in-sample prediction as lagged values. Otherwise use true values.
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
A zipped version of the software site can be downloaded here.
Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.Try NodePit Runner!
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to email@example.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.