Change colors of confusion matrix to shades of blue and change the ax…

…is order to match scikit-learn's (#426) * changing colors of heatmap * changelog * update output labels * update changelog * actually fixing columns to make it the same order as sklearn's * moving reversal of cols to data generation step instead
alteryx · Mar 1, 2020 · 6105522 · 6105522
1 parent 5dba555
commit 6105522
Show file tree

Hide file tree

Showing 2 changed files with 11 additions and 5 deletions.
diff --git a/docs/source/changelog.rst b/docs/source/changelog.rst
@@ -8,6 +8,7 @@ Changelog
         * Add CatBoost (gradient-boosted trees) classification and regression components and pipelines :pr:`247`
         * Added Tuner abstract base class :pr:`351`
         * Added n_jobs as parameter for AutoClassificationSearch and AutoRegressionSearch :pr:`403`
+        * Changed colors of confusion matrix to shades of blue and updated axis order to match scikit-learn's :pr:`426`
     * Fixes
         * Fixed ROC and confusion matrix plots not being calculated if user passed own additional_objectives :pr:`276`
     * Changes

diff --git a/evalml/automl/pipeline_search_plots.py b/evalml/automl/pipeline_search_plots.py
@@ -186,7 +186,10 @@ def get_confusion_matrix_data(self, pipeline_id):
 
         confusion_matrix_data = []
         for fold in cv_data:
-            confusion_matrix_data.append(fold["all_objective_scores"]["Confusion Matrix"])
+            conf_mat = fold["all_objective_scores"]["Confusion Matrix"]
+            # reverse columns in confusion matrix to change axis order to match sklearn's
+            conf_mat = conf_mat.iloc[:, ::-1]
+            confusion_matrix_data.append(conf_mat)
         return confusion_matrix_data
 
     def generate_confusion_matrix(self, pipeline_id, fold_num=None):
@@ -205,15 +208,17 @@ def generate_confusion_matrix(self, pipeline_id, fold_num=None):
 
         conf_mat = data[fold_num]
         labels = conf_mat.columns
+        reversed_labels = labels[::-1]
 
         layout = go.Layout(title={'text': 'Confusion matrix of<br>{} w/ ID={}'.format(pipeline_name, pipeline_id)},
-                           xaxis={'title': 'Predicted Label', 'tickvals': labels},
-                           yaxis={'title': 'True Label', 'tickvals': labels})
-        figure = go.Figure(data=go.Heatmap(x=labels, y=labels, z=conf_mat,
+                           xaxis={'title': 'Predicted Label', 'type': 'category', 'tickvals': labels},
+                           yaxis={'title': 'True Label', 'type': 'category', 'tickvals': reversed_labels})
+        figure = go.Figure(data=go.Heatmap(x=labels, y=reversed_labels, z=conf_mat,
                                            hovertemplate='<b>True</b>: %{y}' +
                                                          '<br><b>Predicted</b>: %{x}' +
                                                          '<br><b>Number of times</b>: %{z}' +
-                                                         '<extra></extra>'),  # necessary to remove unwanted trace info
+                                                         '<extra></extra>',  # necessary to remove unwanted trace info
+                                           colorscale='Blues'),
                            layout=layout)
         return figure