ExplainerComponents

The dashboard is constructed out of ExplainerComponents: self-contained reusable elements usually consisting of a plot or table and various dropdowns, sliders and toggles to manipulate that plot. Components can be connected with connectors, so that when you select an index in one component that automatically updates the index in another component for example.

When you run ExplainerDashboard you get the default dashboard with basically every component listed below with every toggle and slider visible.

The ExplainerComponents make it very easy to construct your own dashboard with your own layout, with specific explanations for the workings and results of your model. So you can select which components to use, where to put them in the layout, which toggles and sliders to display, and what the initial values for component should be. This way you can also control which interactive aspects your end users can and cannot control.

You import the components with from explainerdashboard.custom import *

A simple example, where you build a page with only a ShapDependenceComponent, but with no group cats or highlight toggle, and initial feature set to 'Fare':

from explainerdashboard.custom import *

class CustomDashboard(ExplainerComponent):
   def __init__(self, explainer, title="Custom Dashboard", name="None"):
      super().__init__(explainer, title, name=name)
      self.shap_dependence = ShapDependenceComponent(explainer, name=self.name+"dep",
                         hide_title=True, hide_cats=True, hide_highlight=True,
                         cats=True, col='Fare')

   def layout(self):
      return html.Div([
         self.shap_dependence.layout()
     ])

 ExplainerDashboard(explainer, CustomDashboard).run()

ExplainerComponent

Each component subclasses ExplainerComponent which provides the basic functionality of registering subcomponents, dependencies, registering callbacks of subcomponents, calculating dependencies, and providing a list of pos label selectors of all subcomponents.

ExplainerComponent

.. autoclass:: explainerdashboard.dashboard_methods.ExplainerComponent
   :members:

shap_components

ShapSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.ShapSummaryComponent
   :members:

ShapDependenceComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.ShapDependenceComponent
   :members:

ShapSummaryDependenceConnector

.. autoclass:: explainerdashboard.dashboard_components.shap_components.ShapSummaryDependenceConnector
   :members:

InteractionSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.InteractionSummaryComponent
   :members:

InteractionDependenceComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.InteractionDependenceComponent
   :members:

InteractionSummaryDependenceConnector

.. autoclass:: explainerdashboard.dashboard_components.shap_components.InteractionSummaryDependenceConnector
   :members:

ShapContributionsTableComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.ShapContributionsTableComponent
   :members:

ShapContributionsGraphComponent

.. autoclass:: explainerdashboard.dashboard_components.shap_components.ShapContributionsGraphComponent
   :members:

overview_components

PredictionSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.overview_components.PredictionSummaryComponent
   :members:

ImportancesComponent

.. autoclass:: explainerdashboard.dashboard_components.overview_components.ImportancesComponent
   :members:

FeatureDescriptionsComponent

.. autoclass:: explainerdashboard.dashboard_components.overview_components.FeatureDescriptionsComponent
   :members:

PdpComponent

.. autoclass:: explainerdashboard.dashboard_components.overview_components.PdpComponent
   :members:

FeatureInputComponent

Using the feature input component you can edit the features for a particular observation in order to check what would be the change in prediction if you change one or more features.

You can connect the FeatureInputComponent to the ShapContributionsGraphComponent and the PdpComponent using the``feature_input_component`` parameter:

class WhatIfComposite(ExplainerComponent):
   def __init__(self, explainer, title="What if..."):
      super().__init__(explainer, title, name)

      self.input = FeatureInputComponent(explainer)
      self.contrib = ShapContributionsGraphComponent(explainer, feature_input_component=self.input)
      self.pdp = PdpComponent(explainer, feature_input_component=self.input)

.. autoclass:: explainerdashboard.dashboard_components.overview_components.FeatureInputComponent
   :members:

classifier_components

ClassifierRandomIndexComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.ClassifierRandomIndexComponent
   :members:

ClassifierPredictionSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.ClassifierPredictionSummaryComponent
   :members:

ConfusionMatrixComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.ConfusionMatrixComponent
   :members:

LiftCurveComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.LiftCurveComponent
   :members:

ClassificationComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.ClassificationComponent
   :members:

RocAucComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.RocAucComponent
   :members:

PrAucComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.PrAucComponent
   :members:

PrecisionComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.PrecisionComponent
   :members:

CumulativePrecisionComponent

.. autoclass:: explainerdashboard.dashboard_components.classifier_components.CumulativePrecisionComponent
   :members:

regression_components

RegressionRandomIndexComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.RegressionRandomIndexComponent
   :members:

RegressionPredictionSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.RegressionPredictionSummaryComponent
   :members:

PredictedVsActualComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.PredictedVsActualComponent
   :members:

ResidualsComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.ResidualsComponent
   :members:

RegressionVsColComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.RegressionVsColComponent
   :members:

RegressionModelSummaryComponent

.. autoclass:: explainerdashboard.dashboard_components.regression_components.RegressionModelSummaryComponent
   :members:

decisiontree_components

DecisionTreesComponent

.. autoclass:: explainerdashboard.dashboard_components.decisiontree_components.DecisionTreesComponent
   :members:

DecisionPathTableComponent

.. autoclass:: explainerdashboard.dashboard_components.decisiontree_components.DecisionPathTableComponent
   :members:

DecisionPathGraphComponent

.. autoclass:: explainerdashboard.dashboard_components.decisiontree_components.DecisionPathGraphComponent
   :members:

Connectors

CutoffPercentileComponent

.. autoclass:: explainerdashboard.dashboard_components.connectors.CutoffPercentileComponent
   :members:

PosLabelSelector

.. autoclass:: explainerdashboard.dashboard_methods.PosLabelSelector
   :members:

PosLabelConnector

.. autoclass:: explainerdashboard.dashboard_components.connectors.PosLabelConnector
   :members:

CutoffConnector

.. autoclass:: explainerdashboard.dashboard_components.connectors.CutoffConnector
   :members:

IndexConnector

.. autoclass:: explainerdashboard.dashboard_components.connectors.IndexConnector
   :members:

HighlightConnector

.. autoclass:: explainerdashboard.dashboard_components.connectors.HighlightConnector
   :members: