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  1. Analysis
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Anomaly Edit View

The Anomaly Detection Edit View configures detection settings, sensitivity, and entities, assigning models to specific projects with controlled access.

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Last updated 8 months ago

The Anomaly Detection Edit View in AlphaX Cloud is a user-friendly modal pop-up designed to configure and fine-tune anomaly detection models. Here’s a detailed breakdown of its components:

1. Detection Mode Selection

At the top of the modal, users can choose between two detection modes:

  • Entire Series: Analyzes the entire data series for anomalies.

  • Change Point: Focuses on detecting significant shifts or changes in data patterns over time.

2. Name Field

The Name Field allows users to give the anomaly detection model a descriptive name. This name helps in easily identifying and managing different anomaly detection models.

3. Entity Field

The Entity Field is used to allocate the anomaly detection model to a specific asset or project. By selecting an entity, users ensure that only those with access to that particular asset or project can view and manage the anomaly detection model. This feature is important for maintaining data security and relevance within large organizations.

4. Sensors Selection

In the Sensors section, users can choose which data sets or sensors will be used for the anomaly analysis. This allows for focused monitoring based on specific data streams that are most relevant to the detection model.

5. Show Hidden Channels Checkbox

By checking the Show Hidden Channels box, users can access and select data channels that are usually hidden from normal view but still available for analysis. These channels might include auxiliary data such as battery levels, signal strength, or error codes, which can be critical for certain types of anomaly detection.

6. Sensitivity Slider

The Sensitivity Slider allows users to adjust the sensitivity of the anomaly detection model. Higher sensitivity detects more subtle anomalies, while lower sensitivity focuses on more pronounced deviations, allowing for customized detection based on the specific needs of the user.

7. Max Anomaly Ratio Slider

The Max Anomaly Ratio Slider lets users set the maximum allowable proportion of data points that can be considered anomalies. This parameter helps fine-tune the model to avoid excessive false positives or negatives in the analysis.

8. Save and Cancel Buttons

At the bottom of the modal, users have the option to Save their settings, which applies the configured parameters to the anomaly detection model, or to Cancel and discard any changes.

This modal provides a comprehensive and flexible toolset for users to create and refine anomaly detection models, ensuring accurate monitoring and response to abnormal conditions in their IoT/OT systems while maintaining secure access controls.