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Automatic Evidence-Setting

Context

  • Automatic Evidence-Setting is a function that takes single observations from a dataset or sets of evidence from an Evidence Scenario File and performs inference with the current Bayesian network.
  • So, with Automatic Evidence-Setting, you can inspect — record-by-record — how each individual set of observations/evidence relates to the values inferred through the Bayesian network.
  • If the Bayesian network features a Target Node, Automatic Evidence-Setting compares the inferred values to the observed states.
  • In earlier versions of BayesiaLab, Automatic Evidence-Setting was known as Interactive Inference.

Usage

  • To start Automatic Evidence-Setting, select Main Menu > Inference > Automatic Evidence-Setting.
  • If both an Evidence Scenario File and an associated dataset are available for inference, BayesiaLab prompts you to choose your source:
AutomaticEvidenceSettingEvidenceSource
  • Once Automatic Evidence-Setting is activated, an additional control panel appears in the Toolbar.
ToolbarAutomaticEvidenceSetting

  • This control panel allows you to scroll through the associated dataset or Evidence Scenario File, depending on what you selected.

    • Clicking the button takes you back to the first record, i.e., record 0 in the dataset or scenario 0.

    • The button selects the previous record/scenario.

    • The counter box shows the record/scenario number of the currently displayed set of evidence.

    • The button selects the next record in the dataset/scenario.

    • Clicking takes you to the last record in the dataset/scenario.

    • Click the button to include Not-Observable Nodes for inference, even though they are normally excluded.

    • If you are using an Evidence Scenario File for inference, you can select a specific scenario by right-clicking on the counter box in the control panel. A dropdown list shows all available scenarios in the Evidence Scenario File.

    ControlPanelCounterEvidenceScenario
    • If you are using a dataset that contains a Row Identifier, you can search for a specific record by right-clicking on the counter box in the control panel and entering a search string. You can also use wildcards, i.e., ? to represent a single character and * for any number of characters. Upon pressing Enter, you obtain a list of results, from which you can select a specific record for inference.
    ControlPanelCounterRowIdentified

    • If you scroll through the records associated with a predictive Bayesian network model featuring a Target Node, you can compare the observed states of the Target Node with the states inferred or predicted by the model.

    • For instance, the following Monitors show the observed states for all predictor nodes (highlighted in green) plus the corresponding inferred distribution of the Target Node diagnosis.

    • Here, the inferred probabilities are approximately 75% for Malignant and 25% for Benign. The bar highlighted in silver indicates the actual observation in this particular case, i.e., the ground truth, which is that the sample was indeed Malignant.

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    • Going through records this way, comparing prediction vs. actual states one by one, can help you develop intuition for the sometimes abstract performance measures generated through Network Performance Analysis.

    • Clicking exits the Automatic Evidence-Setting mode.

Workflow Illustration

InferenceAdaptive Questionnaire