- Type: TablePredictions TableTable with prediction and reference column. Must not contain missing values. No timestamp column is necessary but time slots in between predictions should be constant.
This component visualizes how different error metrics change as a forecast horizon grows. Use this component to better understand how far into the future your forecasting model is reliable. A line plot displays the error metrics changing over time. The time on the x-axis is measured in forecast length. Each unit is equal to one record into the future. In fact this component only works on an equally spaced Time Series. For example, if input data is hourly, the forecast length 24 represents one day, 24 hours. If the input data is every two hours it would represent two days, 48 hours. Keep this in mind when interpreting the chart. Metrics on the y-axis displayed in the line plot are cumulative, while metrics displayed in the adjacent tile view are based on the entire input table. All metrics are exported at the output of the component by forecast length.
- Type: TableMetrics TableTable containing cumulative metrics by forecast length.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.4.0
By using or downloading the component, you agree to our terms and conditions.