Properties that can be configured for the HANA Anomaly Detection algorithm.
| Property | Description |
|---|---|
| Output Mode | Select the mode in which you want to use the output of this algorithm. |
| Independent Columns | Select the input source columns. |
| Missing Values | Select the method for handling missing values. Possible
values:
|
| Percentage of Anomalies | Enter the percentage value that indicates the proportion of anomalies in the source data. The default value is 10. |
| Anomaly Detection Method | Select the anomaly detection method.
|
| Maximum Iterations | Enter the number of iterations allowed for finding clusters. The default value is 100. |
| Center Calculation Method | Select the method to use for calculating the initial cluster centers. |
| Normalization Type | Select the type of normalization. |
| Number of Clusters | Enter the number of groups for clustering. |
| Number of Threads | Enter the number of threads that the algorithm should use during execution. The default value is 1. |
| Exit Threshold | Enter the threshold value for exiting from the iterations. The default value is 0.0001. |
| Distance Measure | Enter the measure for calculating the distance between the records and cluster centers. |
| Predicted Column Name | Enter a name for the new column that contains the predicted values. |