02_Forecasting_and_Reconstructing_Time_Series
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This workflow forecasts the monthly average sales in 2017 based on monthly average sales between 2014 and 2016 using dynamic deployment. The forecasting model is an ARIMA (0,1,4) model. The forecasted sales values consist of the forecasted residuals and restored seasonality and trend components.
URL: Time Series Analysis with Components https://www.knime.com/blog/time-series-analysis-with-components
URL: Building a Time Series Application https://www.knime.com/blog/building-a-time-series-analysis-application
URL: Scoring Metrics eBook https://www.knime.com/knimepress/scoring-metrics-evaluating-machine-learning-models
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- FeatureKNIME Data Generation
- FeatureKNIME Javasnippet
- FeatureKNIME Math Expression (JEP)
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