ExplainerTabs¶

There are seven tabs that make up the default``ExplainerDashboard``:

from explainerdashboard.custom import (ImportancesComposite,
                                       ModelSummaryComposite,
                                       IndividualPredictionsComposite,
                                       WhatIfComposite,
                                       ShapDependenceComposite,
                                       ShapInteractionsComposite,
                                       DecisionTreesComposite)

The definitions can be found in the github repo and can serve as a nice starting point for designing your own custom tabs.

ImportancesComposite¶

class explainerdashboard.dashboard_components.composites.ImportancesComposite(explainer, title='Feature Importances', name=None, hide_title=True, hide_importances=False, hide_descriptions=False, hide_selector=True, **kwargs)¶

Overview tab of feature importances

Can show both permutation importances and mean absolute shap values.

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Feature Importances”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide the title
hide_importances (bool, optional) – hide the ImportancesComponent
hide_descriptions (bool, optional) – hide the FeatureDescriptionsComponent
hide_selector (bool, optional) – hide the post label selector. Defaults to True.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

ClassifierModelStatsComposite¶

class explainerdashboard.dashboard_components.composites.ClassifierModelStatsComposite(explainer, title='Classification Stats', name=None, hide_title=True, hide_selector=True, hide_globalcutoff=False, hide_modelsummary=False, hide_confusionmatrix=False, hide_precision=False, hide_classification=False, hide_rocauc=False, hide_prauc=False, hide_liftcurve=False, hide_cumprecision=False, pos_label=None, bin_size=0.1, quantiles=10, cutoff=0.5, **kwargs)¶

Composite of multiple classifier related components:

precision graph
confusion matrix
lift curve
classification graph
roc auc graph
pr auc graph

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Decision Trees”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide title. Defaults to True.
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.
hide_globalcutoff (bool, optional) – hide CutoffPercentileComponent
hide_modelsummary (bool, optional) – hide ClassifierModelSummaryComponent
hide_confusionmatrix (bool, optional) – hide ConfusionMatrixComponent
hide_precision (bool, optional) – hide PrecisionComponent
hide_classification (bool, optional) – hide ClassificationComponent
hide_rocauc (bool, optional) – hide RocAucComponent
hide_prauc (bool, optional) – hide PrAucComponent
hide_liftcurve (bool, optional) – hide LiftCurveComponent
hide_cumprecision (bool, optional) – hide CumulativePrecisionComponent
pos_label ({int, str}, optional) – initial pos label. Defaults to explainer.pos_label
bin_size (float, optional) – bin_size for precision plot. Defaults to 0.1.
quantiles (int, optional) – number of quantiles for precision plot. Defaults to 10.
cutoff (float, optional) – initial cutoff. Defaults to 0.5.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

RegressionModelStatsComposite¶

class explainerdashboard.dashboard_components.composites.RegressionModelStatsComposite(explainer, title='Regression Stats', name=None, hide_title=True, hide_modelsummary=False, hide_predsvsactual=False, hide_residuals=False, hide_regvscol=False, logs=False, pred_or_actual='vs_pred', residuals='difference', col=None, **kwargs)¶

Composite for displaying multiple regression related graphs:

predictions vs actual plot
residual plot
residuals vs feature

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Regression Stats”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide title. Defaults to True.
hide_modelsummary (bool, optional) – hide RegressionModelSummaryComponent
hide_predsvsactual (bool, optional) – hide PredictedVsActualComponent
hide_residuals (bool, optional) – hide ResidualsComponent
hide_regvscol (bool, optional) – hide RegressionVsColComponent
logs (bool, optional) – Use log axis. Defaults to False.
pred_or_actual (str, optional) – plot residuals vs predictions or vs y (actual). Defaults to “vs_pred”.
residuals (str, {'difference', 'ratio', 'log-ratio'} optional) – How to calcualte residuals. Defaults to ‘difference’.
col ({str, int}, optional) – Feature to use for residuals plot. Defaults to None.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

IndividualPredictionsComposite¶

class explainerdashboard.dashboard_components.composites.IndividualPredictionsComposite(explainer, title='Individual Predictions', name=None, hide_predindexselector=False, hide_predictionsummary=False, hide_contributiongraph=False, hide_pdp=False, hide_contributiontable=False, hide_title=False, hide_selector=True, index_check=True, **kwargs)¶

Composite for a number of component that deal with individual predictions:

random index selector
prediction summary
shap contributions graph
shap contribution table
pdp graph

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Individual Predictions”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_predindexselector (bool, optional) – hide ClassifierRandomIndexComponent or RegressionRandomIndexComponent
hide_predictionsummary (bool, optional) – hide ClassifierPredictionSummaryComponent or RegressionPredictionSummaryComponent
hide_contributiongraph (bool, optional) – hide ShapContributionsGraphComponent
hide_pdp (bool, optional) – hide PdpComponent
hide_contributiontable (bool, optional) – hide ShapContributionsTableComponent
hide_title (bool, optional) – hide title. Defaults to False.
index_check (bool, optional) – only pass valid indexes from random index selector to feature input. Defaults to True.
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

WhatIfComposite¶

class explainerdashboard.dashboard_components.composites.WhatIfComposite(explainer, title='What if...', name=None, hide_whatifindexselector=False, hide_inputeditor=False, hide_whatifprediction=False, hide_whatifcontributiongraph=False, hide_whatifpdp=False, hide_whatifcontributiontable=False, hide_title=True, hide_selector=True, index_check=True, n_input_cols=4, sort='importance', **kwargs)¶

Composite for the whatif component:

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Individual Predictions”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide title. Defaults to True.
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.
hide_whatifindexselector (bool, optional) – hide ClassifierRandomIndexComponent or RegressionRandomIndexComponent
hide_inputeditor (bool, optional) – hide FeatureInputComponent
hide_whatifprediction (bool, optional) – hide PredictionSummaryComponent
hide_whatifcontributiongraph (bool, optional) – hide ShapContributionsGraphComponent
hide_whatifcontributiontable (bool, optional) – hide ShapContributionsTableComponent
hide_whatifpdp (bool, optional) – hide PdpComponent
index_check (bool, optional) – only pass valid indexes from random index selector to feature input. Defaults to True.
n_input_cols (int, optional) – number of columns to divide the feature inputs into. Defaults to 4.
sort ({'abs', 'high-to-low', 'low-to-high', 'importance'}, optional) – sorting of shap values. Defaults to ‘importance’.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

ShapDependenceComposite¶

class explainerdashboard.dashboard_components.composites.ShapDependenceComposite(explainer, title='Feature Dependence', name=None, hide_selector=True, hide_shapsummary=False, hide_shapdependence=False, depth=None, **kwargs)¶

Composite of ShapSummary and ShapDependence component

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Feature Dependence”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.
hide_shapsummary (bool, optional) – hide ShapSummaryComponent
hide_shapdependence (bool, optional) – ShapDependenceComponent
depth (int, optional) – Number of features to display. Defaults to None.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

ShapInteractionsComposite¶

class explainerdashboard.dashboard_components.composites.ShapInteractionsComposite(explainer, title='Feature Interactions', name=None, hide_selector=True, hide_interactionsummary=False, hide_interactiondependence=False, depth=None, **kwargs)¶

Composite of InteractionSummaryComponent and InteractionDependenceComponent

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Feature Interactions”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.
hide_interactionsummary (bool, optional) – hide InteractionSummaryComponent
hide_interactiondependence (bool, optional) – hide InteractionDependenceComponent
depth (int, optional) – Initial number of features to display. Defaults to None.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

DecisionTreesComposite¶

class explainerdashboard.dashboard_components.composites.DecisionTreesComposite(explainer, title='Decision Trees', name=None, hide_treeindexselector=False, hide_treesgraph=False, hide_treepathtable=False, hide_treepathgraph=False, hide_selector=True, index_check=True, **kwargs)¶

Composite of decision tree related components:

index selector
individual decision trees barchart
decision path table
deciion path graph

Parameters

explainer (Explainer) – explainer object constructed with either RandomForestClassifierExplainer() or RandomForestRegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Decision Trees”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_treeindexselector (bool, optional) – hide ClassifierRandomIndexComponent or RegressionRandomIndexComponent
hide_treesgraph (bool, optional) – hide DecisionTreesComponent
hide_treepathtable (bool, optional) – hide DecisionPathTableComponent
hide_treepathgraph (bool, optional) – DecisionPathGraphComponent
hide_selector (bool, optional) – hide all pos label selectors. Defaults to True.
index_check (bool, optional) – only pass valid indexes from random index selector to feature input. Defaults to True.

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

SimplifiedClassifierComposite¶

screenshot

_images/simple_classifier_dashboard.png

You can also load this composite with:

explainer = ClassifierExplainer(model, X, y)
ExplainerDashboard(explainer, simple=True)

class explainerdashboard.dashboard_components.composites.SimplifiedClassifierComposite(explainer, title='Simple Classifier Explainer', name=None, hide_title=False, classifier_custom_component='roc_auc', hide_confusionmatrix=False, hide_classifier_custom_component=False, hide_shapsummary=False, hide_shapdependence=False, hide_predindexselector=False, hide_predictionsummary=False, hide_contributiongraph=False, **kwargs)¶

Composite of multiple classifier related components, on a single tab:

confusion matrix
one other model quality indicator: choose from pr auc graph, precision graph,
lift curve, classification graph, or roc auc graph
shap importance
shap dependence
index selector
index prediction summary
index shap contribution graph

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Simple Classification Stats”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide the title. Defaults to False.
classifier_custom_component (str, optional) – custom classifier quality indicator supported by the ClassifierExplainer object. Valid values are: ‘roc_auc’, ‘metrics’, pr_auc’, ‘precision_graph’, ‘lift_curve’, ‘classification’. Defaults to ‘roc_auc’.
hide_confusionmatrix (bool, optional) – hide ConfusionMatrixComponent
hide_classifier_custom_component (bool, optional) – hide the chosen classifier_custom_component
hide_shapsummary (bool, optional) – hide ShapSummaryComponent
hide_shapdependence (bool, optional) – hide ShapDependenceComponent
hide_predindexselector (bool, optional) – hide ClassifierRandomIndexComponent or RegressionRandomIndexComponent
hide_predictionsummary (bool, optional) – hide ClassifierPredictionSummaryComponent or RegressionPredictionSummaryComponent
hide_contributiongraph (bool, optional) – hide ShapContributionsGraphComponent

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

SimplifiedRegressionComposite¶

screenshot

_images/simple_regression_dashboard.png

You can also load this composite with:

explainer = RegressionExplainer(model, X, y)
ExplainerDashboard(explainer, simple=True)

class explainerdashboard.dashboard_components.composites.SimplifiedRegressionComposite(explainer, title='Simple Regression Explainer', name=None, hide_title=False, regression_custom_component='vs_col', hide_goodness_of_fit=False, hide_regression_custom_component=False, hide_shapsummary=False, hide_shapdependence=False, hide_predindexselector=False, hide_predictionsummary=False, hide_contributiongraph=False, **kwargs)¶

Composite of multiple classifier related components, on a single tab:

goodness of fit component
one other model quality indicator: ‘metrics’, ‘residuals’ or’residuals_vs_col’
shap importance
shap dependence
index selector
index prediction summary
index shap contribution graph

Parameters

explainer (Explainer) – explainer object constructed with either ClassifierExplainer() or RegressionExplainer()
title (str, optional) – Title of tab or page. Defaults to “Simple Classification Stats”.
name (str, optional) – unique name to add to Component elements. If None then random uuid is generated to make sure it’s unique. Defaults to None.
hide_title (bool, optional) – hide the title. Defaults to False.
regression_custom_component (str, optional) – custom classifier quality indicator supported by the ClassifierExplainer object. Valid values are: ‘metrics’, ‘residuals’ or’vs_col’
hide_goodness_of_fit (bool, optional) – hide goodness of fit component
hide_regression_custom_component (bool, optional) – hide the chosen regression_custom_component
hide_shapsummary (bool, optional) – hide ShapSummaryComponent
hide_shapdependence (bool, optional) – hide ShapDependenceComponent
hide_predindexselector (bool, optional) – hide RegressionRandomIndexComponent or RegressionRandomIndexComponent
hide_predictionsummary (bool, optional) – hide RegressionPredictionSummaryComponent or RegressionPredictionSummaryComponent
hide_contributiongraph (bool, optional) – hide ShapContributionsGraphComponent

layout()¶: layout to be defined by the particular ExplainerComponent instance. All element id’s should append +self.name to make sure they are unique.

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

ExplainerTabsLayout¶

class explainerdashboard.dashboards.ExplainerTabsLayout(explainer, tabs, title='Model Explainer', name=None, description=None, header_hide_title=False, header_hide_selector=False, header_hide_download=False, hide_poweredby=False, block_selector_callbacks=False, pos_label=None, fluid=True, **kwargs)¶

Generates a multi tab layout from a a list of ExplainerComponents. If the component is a class definition, it gets instantiated first. If the component is not derived from an ExplainerComponent, then attempt with duck typing to nevertheless instantiate a layout.

Parameters

explainer ([type]) – explainer
tabs (list[ExplainerComponent class or instance]) – list of ExplainerComponent class definitions or instances.
title (str, optional) – [description]. Defaults to ‘Model Explainer’.
description (str, optional) – description tooltip to add to the title.
header_hide_title (bool, optional) – Hide the title. Defaults to False.
header_hide_selector (bool, optional) – Hide the positive label selector. Defaults to False.
header_hide_download (bool, optional) – Hide the download link. Defaults to False.
hide_poweredby (bool, optional) – hide the powered by footer
block_selector_callbacks (bool, optional) – block the callback of the pos label selector. Useful to avoid clashes when you have your own PosLabelSelector in your layout. Defaults to False.
pos_label ({int, str}, optional) – initial pos label. Defaults to explainer.pos_label
fluid (bool, optional) – Stretch layout to fill space. Defaults to False.

layout()¶: returns a multitab layout plus ExplainerHeader

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

register_callbacks(app)¶: Registers callbacks for all tabs

calculate_dependencies()¶: Calculates dependencies for all tabs

ExplainerPageLayout¶

class explainerdashboard.dashboards.ExplainerPageLayout(explainer, component, title='Model Explainer', name=None, description=None, header_hide_title=False, header_hide_selector=False, header_hide_download=False, hide_poweredby=False, block_selector_callbacks=False, pos_label=None, fluid=False, **kwargs)¶

Generates a single page layout from a single ExplainerComponent. If the component is a class definition, it gets instantiated.

If the component is not derived from an ExplainerComponent, then tries with duck typing to nevertheless instantiate a layout.

Parameters

explainer ([type]) – explainer
component (ExplainerComponent class or instance) – ExplainerComponent class definition or instance.
title (str, optional) – Defaults to ‘Model Explainer’.
description (str, optional) – Will be displayed as title tooltip.
header_hide_title (bool, optional) – Hide the title. Defaults to False.
header_hide_selector (bool, optional) – Hide the positive label selector. Defaults to False.
header_hide_download (bool, optional) – Hide the download link. Defaults to False.
hide_poweredby (bool, optional) – hide the powered by footer
block_selector_callbacks (bool, optional) – block the callback of the pos label selector. Useful to avoid clashes when you have your own PosLabelSelector in your layout. Defaults to False.
pos_label ({int, str}, optional) – initial pos label. Defaults to explainer.pos_label
fluid (bool, optional) – Stretch layout to fill space. Defaults to False.

layout()¶: returns single page layout with an ExplainerHeader

to_html(state_dict=None, add_header=True)¶

return static html for this component and all subcomponents.

Parameters: state_dict (dict) – dictionary with id_prop_tuple as keys and state as value.

register_callbacks(app)¶: Register callbacks of page

calculate_dependencies()¶: Calculate dependencies of page