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    Forecast Accuracy
    • 13 Jan 2023
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    Contents

    Forecast Accuracy

    • Updated on 13 Jan 2023
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    Article summary

    Description

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


    Configuration Options

    Basic Configuration Options

    SettingDescription\Parameters
    Split ColumnsThe selected columns split the data set up when calculating summary metrics.
    Sort By ColumnsSort data rows by these columns.
    Target ColumnActuals data column.
    Forecast ColumnForecast data column.
    Role ColumnSplits the data set into scoring and training data.
    Training ValueValue in the Role Column for training data.
    Scoring ValueValue is the Role Column for scoring data.
    Time GranularityLength 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 MAEA performance setting that uses the same set of actuals to calculate the scaled MAE when performing a MASE calculation.
    MetricsSelected 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 WinnersProduce 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

    ActionDescription
    PreviewOnce the node is configured, the combined result set can be previewed at any time.
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