Forecast Accuracy
Last updated: 13 Jan 2023
Description¶
The Forecast Accuracy node calculates a set of metrics from actuals/forecast data.
Configuration Options¶
Basic Configuration Options¶
| Setting | Description\Parameters |
|---|---|
Split Columns |
The selected columns split the data set up when calculating summary metrics. |
Sort By Columns |
Sort data rows by these columns. |
Target Column |
Actuals data column. |
Forecast Column |
Forecast data column. |
Role Column |
Splits the data set into scoring and training data. |
Training Value |
Value in the Role Column for training data. |
Scoring Value |
Value is the Role Column for scoring data. |
Time Granularity |
Length of time between records in the input data set. I.e., if each input record represents a week of data, the time granularity is Week. Options |
- Day
- Week
- Month
- Quarter
- Year
Cache Training MAE| A performance setting that uses the same set of actuals to calculate the scaled MAE when performing a MASE calculation. |
|Metrics|Selected metrics to calculate. Options
- Mean Forecast Error
- Mean Absolute Error
- Mean Absolute Percent Error
- Mean Squared Error
- Root Mean Squared Error
- Mean Absolute Scaled Error
|
|Select MASE Winners| Produce a WINNER_COLUMN and WINNER_FORECAST column based on which model produces the most accurate forecast/lowest MASE value.
Options
- Top 1
- Top 3
- None
Actions¶
| Action | Description |
|---|---|
Preview |
Once the node is configured, the combined result set can be previewed at any time. |