Icon

02_​Forecasting_​and_​Reconstructing_​Time_​Series

Forecasting and Reconstructing Time Series
Dynamic forecasting and reconstructing the signal Access seasonality lag and trend model Forecast Restore seasonality and trend Assess forecast accuracy Yearly SeasonalityTrendARIMASeasonalitiesseed dataTraining dataReal data for scoring Trend model Restore Seasonality Line color Restore Trend Line Plot Numeric Scorer RowID Loop Deployment Table Reader Table Reader Table Reader Table Reader Table Rowto Variable PMML Reader Joiner Dynamic forecasting and reconstructing the signal Access seasonality lag and trend model Forecast Restore seasonality and trend Assess forecast accuracy Yearly SeasonalityTrendARIMASeasonalitiesseed dataTraining dataReal data for scoring Trend model Restore Seasonality Line color Restore Trend Line Plot Numeric Scorer RowID Loop Deployment Table Reader Table Reader Table Reader Table Reader Table Rowto Variable PMML Reader Joiner

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Maarit Laukkanen
Created at: 2020-06-09
On NodePit since: 2021-10-24
Last update: 2024-04-28
Created with KNIME version: v4.4.0
Tags: dynamic deploymentrecursive loopARIMArestore seasonalityrestore trend

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!