Forecast Accuracy

Description

The Forecast Accuracy node calculates a set of metrics from actuals/forecast data.

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

Action	Description
`Preview`	Once the node is configured, the combined result set can be previewed at any time.