Data Screening Options

Data Screening options enable you to select several ways of handling missing values, identifying and adjusting outliers, and including events in predictions.

Historical data can have missing values and outliers, which are data points that differ significantly from the rest of the data, or can include events, which are typically one-off or recurring events that historically led to spikes or declines in the data. Because adjusted outliers are treated as missing values, both of these situations are discussed and handled together.

Select from these options for Data Screening.

• Adjust Outliers—When this option is selected, when an outlier is detected in the series, outlier values are replaced with the prediction trend line value to avoid the impact of outliers.
• Fill in missing values—When this option is selected, if there are missing values in the time series, the missing values are populated with the prediction trend line value to continue with the prediction.
• Minimum missing threshold—When this option is selected, missing values in the time series are filled until the threshold is met. If the number of missing values is above the threshold provided, the prediction is not done. The maximum value can't be greater than 50%.