# Anomaly Over Space
URL: https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/experiment-insights/anom-over-space.html

> Maps anomaly scores based on a dataset's location features.

# Anomaly Over Space

| Tab | Description |
| --- | --- |
| Performance | Displays anomalous score values on a unique map based on the validation partition. |

Anomaly Over Space maps anomaly scores based on a dataset's location (geospatial) features. Co-located points are displayed using the average value of all points at that location.

The following table describes the settings:

| Setting | Description |
| --- | --- |
| Visualization | Sets the map type for the visualization. |
| Aggregation | Sets the arithmetic to use for co-located locations, either avg, min, max, count, or value.Count reports the count of each geometry in the dataset, or for a hexagon or grid map of a geometry feature, it reports the sum of counts.Value displays the feature value (no aggregation) when all geometries have a count of 1. |
| Data selection | Sets which data partition to visualize, either validation, cross-validation, or holdout. |
| Metric type | Sets the value to report at each location as Predicted. Other options are not available because anomaly detection is based on unsupervised modeling. |
| Visualization settings | Allows you to set a variety of map viewing settings, including opacity, coverage, elevation scale, percentile, radius, and intensity. |

## Map visualizations

The following map-type options are available from the Visualization dropdown.

### Unique map

The Unique map shows individual unique points on the map. If points are on the same location, that information is reflected in the "Count" column of the tooltip shown when hovering over a point.

### Kernel density map

A Kernel density map collects multiple observations within each given kernel and displays aggregated statistics with a color gradient. For location features, the count, min, max, and average can be selected from the Aggregation dropdown. For numeric features, the min, max, or average is available. For categorical features, the mode is displayed. Several visualization customizations are available in Visualization Settings.

### Hexagon map

Select Hexagon map to display data as hexagon-shaped cells. When selecting Aggregation settings:

- For location features, count, min, max, and average are available.
- For numeric features, min, max, or average are available.
- For categorical features, the mode is displayed.

Use the Visualization settings in the bottom-right of the map panel to adjust the settings.

### Heat map

You can also view heat map visualizations for geometry and numeric features. The heat map visualization is not available for categorical features. Select Heatmap from the Visualization dropdown at the bottom-left of the map panel. Use the Visualization settings in the bottom-right of the map panel to adjust the settings.

## Visualization settings

The following settings are available in the Visualization settings dropdown, with the selection being dependent on map type. The following table describes each setting:

| Setting | Description |
| --- | --- |
| Coverage | Sets the percentage of the radius that the hexagon displayed on the map occupies. The full cluster/hexagon is of width Radius.The hexagon displayed on the map occupies Coverage % at the center of the full hexagon. |
| Elevation scale | Controls the scale of how tall the clusters can be. |
| Intensity | Modifies the intensity of the color of each pixel; used by the heat map. |
| Opacity | Adjusts transparency of layers. |
| Percentile | As the slider moves, it removes a portion, by percentile, from the map. This setting is helpful for identifying outliers. |
| Radius | Controls the radius of the hexagon clusters; this is the precision of the aggregation. |

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