Viewing reactions marked by members to Machine Learning (ML) insights

You can view the reactions that members of a project mark to show their agreement or disagreement with the insights into the parameters.

Before you begin

You must have completed the following tasks:

Procedure

  1. Log in to HCL OneTest Server.

    The team space that contains your project is displayed.

  2. Click Active projects > My projects > project_name to open the project that contains the test assets.

    The Overview page of the project is displayed.

  3. Click Analyze > Insights in the navigation pane.

    The Insights page is displayed.

  4. Identify the test asset or the parameter by performing any of the following actions:
    • Search for the test asset or parameter by entering any text contained in its name in the Search field.
    • Sort the items in the table of insights by clicking any of the column headers, and then identifying the insight.

      For example, you can sort the items based on the name of the test asset in an ascending order or descending order, and then identify the test that you ran.

    You identified the insight.

  5. Use the information in the following table to interpret the reactions marked for the insight:
    If the icon is displayed as Interpretation of the reaction
    Image of the agree icon. None of the members agreed with the insight.
    Image of the icon changed when agreed. At least one member agreed with the insight.
    Note: The name of the member who reacted is displayed as Agreed by username when you hover over the icon.
    Image of the disagree icon. None of the members disagreed with the insight.
    Image of the icon changed when disagreed. At least one member disagreed with the insight.
    Note: The name of the member who reacted is displayed as Disagreed by username when you hover over the icon.

Results

You viewed the member reactions to an insight from the Insights page.

What to do next

You can perform any of the following tasks:
  • Modify the threshold value of a specific parameter based on the number of disagreements marked by members so that you can improve the accuracy of the insight. See Modifying Machine Learning analyzer settings.
  • Repeat the test runs with the updated thresholds to improve the Machine Learning insights for the specific parameter. See Test run configurations.