updated release notes

RELEASE_NOTES.md

@@ -12,10 +12,11 @@
     configuration of your explainer/dashboard to file.
 -   explainerdashboard CLI:
     - Start an explainerdashboard from the command-line!
-    - start default dashboard from stored explainer : `explainerdashboard explainer.joblib`
-    - start dashboard from config: `explainerdashboard explainerdashboard.yaml`
+    - start default dashboard from stored explainer : `explainerdashboard run explainer.joblib`
+    - start full configured dashboard from config: `explainerdashboard run explainerdashboard.yaml`
+    - build explainer based on input files defined in .yaml 
+        (model.pkl, data.csv, etc): `explainerdashboard build explainerdashboard.yaml`
     - includes new ascii logo :)
-    - can also build explainer from model.pkl, data.csv and config
 
 ### Bug Fixes
 -
@@ -24,6 +25,8 @@
 ### Improvements
 -   If idxs is not passed use X.index instead
 -   explainer.idxs performance enhancements
+-   added whatif component and tab to InlineExplainer
+-   added cumulative precision component to InlineExplainer
 
 ### Other Changes
 -

TODO.md

@@ -25,8 +25,7 @@
 - add plain language explanations
 - rename RandomForestExplainer and XGBExplainer methods into something more logical
     - Breaking change!
-- Add whatif to InlineExplainer
-- Add cumulativeprecisionplot to InlineExplainer
+
 
 ## notebooks:
 
@@ -65,9 +64,6 @@
         self.register_components(self.connector)
 
 ## Library level:
-- add explainerdashboard commandline tool: add entry_points to setup.py
 - Add Altair (vega) plots for easy inclusion in websites or fastpages blogs
-- Long term: add option to load from directory with pickled model, data csv and config file
 - add more screenshots to README with https://postimages.org/
-- submit pull request to shap with broken test for https://github.com/slundberg/shap/issues/723
-- install vscode github pull requests and issues extension
+- submit pull request to shap with broken test for https://github.com/slundberg/shap/issues/723

explainerdashboard/dashboard_components/classifier_components.py

@@ -366,13 +366,13 @@ def update_precision_graph(cutoff, percentage, pos_label):
 class CumulativePrecisionComponent(ExplainerComponent):
     def __init__(self, explainer, title="Cumulative Precision", name=None,
                     hide_selector=False, pos_label=None):
-        """Show liftcurve component
+        """Show cumulative precision component
 
         Args:
             explainer (Explainer): explainer object constructed with either
                         ClassifierExplainer() or RegressionExplainer()
             title (str, optional): Title of tab or page. Defaults to 
-                        "Lift Curve".
+                        "Cumulative Precision".
             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.

explainerdashboard/dashboards.py

@@ -582,7 +582,7 @@ def to_yaml(self, filepath=None, return_dict=False):
                 config.
         """
         import oyaml as yaml
-        
+
         explainer_config = self.explainer.to_yaml(return_dict=True)
         dashboard_config = dict(
             dashboard=dict(
@@ -718,6 +718,13 @@ def pdp(self, title="Partial Dependence Plots", **kwargs):
         comp = PdpComponent(self._explainer, **kwargs)
         self._run_component(comp, title)
 
+    @delegates_kwargs(WhatIfComponent)
+    @delegates_doc(WhatIfComponent)
+    def whatif(self, title="What if...", **kwargs):
+        """Show What if... component inline in notebook"""
+        comp = WhatIfComponent(self._explainer, **kwargs)
+        self._run_component(comp, title)
+
 
 class InlineExplainerComponent:
     def __init__(self, inline_explainer, name):
@@ -757,6 +764,13 @@ def contributions(self,  title='Contributions', **kwargs):
         """Show contributions (permutation or shap) inline in notebook"""
         tab = ContributionsTab(self._explainer, **kwargs)
         self._run_component(tab, title)
+
+    @delegates_kwargs(WhatIfTab)
+    @delegates_doc(WhatIfTab)
+    def whatif(self,  title='What if...', **kwargs):
+        """Show What if... tab inline in notebook"""
+        tab = WhatIfTab(self._explainer, **kwargs)
+        self._run_component(tab, title)
 
     @delegates_kwargs(ShapDependenceTab)
     @delegates_doc(ShapDependenceTab)
@@ -856,6 +870,14 @@ def precision(self, title="Precision Plot", **kwargs):
         comp = PrecisionComponent(self._explainer, **kwargs)
         self._run_component(comp, title)
 
+    @delegates_kwargs(CumulativePrecisionComponent)
+    @delegates_doc(CumulativePrecisionComponent)
+    def cumulative_precision(self, title="Cumulative Precision Plot", **kwargs):
+        """shows cumulative precision plot"""
+        assert self._explainer.is_classifier
+        comp = CumulativePrecisionComponent(self._explainer, **kwargs)
+        self._run_component(comp, title)
+
     @delegates_kwargs(ConfusionMatrixComponent)
     @delegates_doc(ConfusionMatrixComponent)
     def confusion_matrix(self, title="Confusion Matrix", **kwargs):