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The option to create this chart will be disabled unless your query contains a temporal grouping with no columns fields added as arguments. Furthermore, your query must contain a numeric column field (for example, you can aggregate your data and add a count).
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Go to Data Search and open the required table.
Perform the required operations to get the data you want to use in the chart.
After getting the required query results, go to Additional tools → Charts → Anomaly Detection → Robust Random Cut Forest.
Drag the required columns fields to their corresponding fields. This chart requires you to select the following fields:
The Robust Random Cut Forest chart is displayed.  |
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You will not be able to train your model if the data series contains holes due to non-existing events. In this case, the chart would try to interpolate those missing points. The interpolation takes into account the average of n previous points to allow working in real-time. When interpolation occurs, gaps are filled with purple dots to indicate that you are visualizing generated values. The maximum number of consecutive missing points to be interpolated is 5. If this value is exceeded, you will not be able to train the model. An error will appear when clicking the Train button and holes will be marked in the chart with pinkish bands.
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Interpolation only works with events that don't exist. The chart will never interpolate values from data yet to be loaded. These areas are represented on the chart as gray bands. In this case, the chart will only evaluate up to the first gap. There must be enough events for at least training and evaluating one point before the gap starts, otherwise, you will be notified. Click the Download more button in the warning message that appears to download the data required for the widget to train, or do it manually activating the Load all events option in the Event loading indicator of the search window. If you wish to fill certain areas where gaps are located, you can do so by clicking on the event timeline at the top of the search window. Learn more about loading data in the search window here. |